{"id":"W6962161648","doi":"10.15468/dl.twxt98","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Salmo; Range (aeronautics); Identification (biology); Download","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":[0.0009492424,0.002157223,0.001687251,0.005341341,0.001002112,0.002718705,0.002896657,0.001896627,0.1665316],"category_scores_gemma":[0.005729833,0.001034665,0.00132536,0.01096385,0.0004414532,0.002320291,0.002734916,0.001956674,0.2363859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001600658,"about_ca_system_score_gemma":0.002537247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02397749,"about_ca_topic_score_gemma":0.03970742,"domain_scores_codex":[0.9988758,0.000142518,0.0001475607,0.0004015006,0.0002505687,0.0001820581],"domain_scores_gemma":[0.9975722,0.0006376587,0.000233251,0.0006562484,0.00062432,0.0002763106],"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":[0.00003367855,0.000009803867,0.0003445271,0.0005548919,0.00001663464,0.00001397344,0.00002246191,0.0001094043,0.0001286661,0.000419855,0.9968772,0.001468958],"study_design_scores_gemma":[0.00006616711,0.000007072791,0.001563202,0.0001634138,0.00001492319,0.00003415138,0.00005131259,0.0001144425,0.0001921236,0.0008095813,0.9969657,0.00001786009],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003575268,0.00002672993,0.00004649378,0.00002837225,0.00001057309,0.000004549207,0.9987577,0.0004199844,0.0006698052],"genre_scores_gemma":[0.0001365122,0.0000346774,0.0001972083,0.00004343054,0.000002961243,0.00003634655,0.9988944,0.0001813306,0.0004732013],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8334684,"threshold_uncertainty_score":0.5571036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}