{"id":"W6887190941","doi":"10.15468/dl.t5zgb4","title":"Occurrence Download","year":2019,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geodetic datum; Matching (statistics); Download; Range (aeronautics); Coordinate system","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":[0.0009087108,0.001754346,0.001577651,0.005359347,0.001041395,0.002603751,0.002715228,0.001813242,0.1528105],"category_scores_gemma":[0.005376899,0.0008630555,0.001113506,0.01090708,0.0004317469,0.002124771,0.002553963,0.001862162,0.2240191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001511749,"about_ca_system_score_gemma":0.002410439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02344673,"about_ca_topic_score_gemma":0.03887705,"domain_scores_codex":[0.9989597,0.0001318121,0.0001324265,0.0003500721,0.0002403873,0.0001855883],"domain_scores_gemma":[0.9977068,0.0006007359,0.0002284418,0.0006131508,0.0005857017,0.0002650871],"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":[0.00002780388,0.00001044629,0.000446418,0.0004907316,0.00001511041,0.0000160897,0.00002888663,0.000122382,0.0001267882,0.0004121626,0.9966731,0.001630203],"study_design_scores_gemma":[0.00005233952,0.000006961294,0.002054812,0.0001699704,0.0000133942,0.00003721948,0.00008461801,0.0001291248,0.0001799721,0.0006789024,0.9965764,0.00001634486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004691651,0.00002649572,0.00004582318,0.00003125469,0.00001218503,0.000004266795,0.9988061,0.0003689594,0.0006579574],"genre_scores_gemma":[0.0001573233,0.00002991808,0.0001815358,0.00003428561,0.000003067491,0.00003120139,0.9989421,0.0001390602,0.0004816388],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8471895,"threshold_uncertainty_score":0.511202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}