The evaluation metric for this competition is the samples-averaged \\(F\_1\\)-score, which measures an overlap between the predicted and actual set of species present at a given location and time. Each test PA sample \\( i \\) is associated with a set of ground-truth labels \\( Y\_i \\), i.e., the set of plant species (=speciesId). For each sample, the submission must provide a list of labels, i.e., the set of species predicted present \\( \\widehat{Y}\_{i,1}, \\widehat{Y}\_{i,2}, \\dots, {\\widehat{Y}}\_{i,R\_i} \\). The micro \\(F\_1\\)-score is then computed using

\\\[ F\_1 = \\frac{1}{N} \\sum\_{i=1}^N \\frac{\\text{TP}\_i}{\\text{TP}\_i+(\\text{FP}\_i+\\text{FN}\_i)/2} \\\\ \\quad \\text{Where} \\begin{cases} \\text{TP}\_i =\\text{ Number of predicted species truly present, i.e. }|\\widehat{Y}\_i \\cap Y\_i |\\\\ \\text{FP}\_i =\\text{ Number of species predicted but absent, i.e. } |\\widehat{Y}\_i \\setminus Y\_i | \\\\ \\text{FN}\_i =\\text{ Number of species not predicted but present, i.e. } | Y\_i \\setminus \\widehat{Y}\_i |\\\\ \\end{cases} \\\]