{"id":"W6961945119","doi":"10.15468/dl.bmepm7","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); 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":[0.000930986,0.002331019,0.001539621,0.004526678,0.001011882,0.002483897,0.003064317,0.001996275,0.1249181],"category_scores_gemma":[0.005827121,0.0009059134,0.001283872,0.008708935,0.0004642354,0.002292097,0.002475684,0.001974503,0.1802012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668008,"about_ca_system_score_gemma":0.002461347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02312365,"about_ca_topic_score_gemma":0.04059695,"domain_scores_codex":[0.9989617,0.0001442125,0.0001378291,0.0003742417,0.0002302873,0.0001518012],"domain_scores_gemma":[0.9978291,0.0006090782,0.0001943267,0.0005614311,0.0005491292,0.0002569044],"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":[0.00003723753,0.00001466879,0.0004335721,0.0005228494,0.00001643717,0.00001816166,0.00002312788,0.0001625934,0.0001185506,0.0004274603,0.9966233,0.00160205],"study_design_scores_gemma":[0.00008692284,0.00001025224,0.00168512,0.0001708172,0.00001521543,0.00004864054,0.00006963277,0.000247602,0.0002256394,0.0009357464,0.9964852,0.00001922706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006433357,0.00003812841,0.0000625398,0.00004183579,0.00001332637,0.000006578859,0.9983717,0.0006497617,0.0007519348],"genre_scores_gemma":[0.0001762284,0.00003671537,0.0002543596,0.00004524464,0.000003010336,0.00003477145,0.9988394,0.0001702421,0.0004400003],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8750819,"threshold_uncertainty_score":0.4178927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01354698637645786,"score_gpt":0.2538377714956856,"score_spread":0.2402907851192278,"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."}}