{"id":"W6887177351","doi":"10.15468/dl.tm7ade","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Ichthyology; Barcode; Matching (statistics); Fish <Actinopterygii>; Range (aeronautics)","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":[0.001093304,0.002214627,0.001845723,0.006205525,0.001234647,0.003094115,0.003050277,0.002190343,0.2302645],"category_scores_gemma":[0.007294061,0.001180347,0.00140082,0.01120409,0.0004576835,0.002990239,0.003338557,0.002129475,0.2979343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001701202,"about_ca_system_score_gemma":0.002595969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01948016,"about_ca_topic_score_gemma":0.0323421,"domain_scores_codex":[0.9987119,0.0001544946,0.0001776038,0.0004609304,0.0002781758,0.0002167859],"domain_scores_gemma":[0.9971347,0.0007844222,0.0002444913,0.0007253612,0.0007781991,0.0003327661],"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":[0.00003198097,0.000009995073,0.0003359858,0.0006473865,0.00001470721,0.00001567482,0.00002518908,0.00008828579,0.0001127255,0.0003475788,0.9967438,0.001626571],"study_design_scores_gemma":[0.00006999473,0.00000747536,0.001422687,0.0002069722,0.00001356387,0.00003647064,0.00007091997,0.0001088432,0.0001645094,0.0006798998,0.9972007,0.00001781077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003034448,0.00002365817,0.00004898843,0.00003106201,0.00001189467,0.000005922134,0.9987382,0.000452516,0.0006575097],"genre_scores_gemma":[0.000134194,0.00003707899,0.0002420523,0.0000470899,0.000004076284,0.00005444171,0.9986928,0.0002415492,0.0005467955],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7697355,"threshold_uncertainty_score":0.7703115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}