{"id":"W6962701494","doi":"10.15468/dl.r2rqsb","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Download; Set (abstract data type); Identification (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009576068,0.002165026,0.001574984,0.004940291,0.000942154,0.002630292,0.002771444,0.002136475,0.1567635],"category_scores_gemma":[0.005898865,0.0008512748,0.001199845,0.009310079,0.0004627218,0.002178904,0.002351047,0.001946499,0.2151085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165696,"about_ca_system_score_gemma":0.00237885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01793323,"about_ca_topic_score_gemma":0.03146811,"domain_scores_codex":[0.9989673,0.0001508362,0.0001362849,0.0003672295,0.0002191799,0.0001591368],"domain_scores_gemma":[0.9977002,0.0007049261,0.0002272398,0.0005379414,0.000544793,0.0002848098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003684489,0.00001221944,0.0003749467,0.0005644302,0.00001469255,0.00001567741,0.00001817395,0.0001379121,0.0001058384,0.0003782789,0.996917,0.001424003],"study_design_scores_gemma":[0.00008409303,0.000009975591,0.001513121,0.0001941662,0.000015137,0.00003964542,0.00005431085,0.0001676618,0.0001868247,0.0008586147,0.9968588,0.00001767272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000398979,0.00003311048,0.00003830867,0.00003765186,0.00001187151,0.000005023878,0.9988685,0.0003253446,0.0006403383],"genre_scores_gemma":[0.0001603594,0.0000422259,0.0001901671,0.00005429514,0.000003834274,0.00003858942,0.9988702,0.0001278693,0.0005123453],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8432364,"threshold_uncertainty_score":0.5244263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02358343866178237,"score_gpt":0.2689055240188922,"score_spread":0.2453220853571099,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}