{"id":"W6887152199","doi":"10.15468/dl.v5vy3p","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":"Matching (statistics); Download; Alien; Range (aeronautics); State (computer science)","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":[0.0009389914,0.001997674,0.001510437,0.004965358,0.001008894,0.002532131,0.002629456,0.001986134,0.1618095],"category_scores_gemma":[0.00609966,0.000887336,0.001196268,0.009870889,0.0004438402,0.002167261,0.002465556,0.001821321,0.217498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480476,"about_ca_system_score_gemma":0.00233797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02091387,"about_ca_topic_score_gemma":0.0339605,"domain_scores_codex":[0.9989622,0.0001459117,0.000130748,0.0003695305,0.0002189475,0.0001726394],"domain_scores_gemma":[0.9975473,0.0007248238,0.0002321484,0.0006049264,0.0006219894,0.0002688983],"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":[0.00003231732,0.00001178189,0.0004090306,0.0005587602,0.00001409981,0.00001510163,0.00002153946,0.0001252691,0.0001229545,0.0003604006,0.9968697,0.001459081],"study_design_scores_gemma":[0.00007670518,0.00001059015,0.001899873,0.0001982607,0.00001518827,0.00003789253,0.00006853327,0.0001484189,0.0001975746,0.0007830348,0.996545,0.00001876206],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000465772,0.00002897646,0.00003970009,0.00003450266,0.00001243198,0.000005199311,0.9988317,0.0003548687,0.0006461552],"genre_scores_gemma":[0.0001654143,0.00003537765,0.000187521,0.00004689903,0.000003774696,0.00004346938,0.9988901,0.0001420374,0.0004853263],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8381905,"threshold_uncertainty_score":0.5413067,"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."}}