{"id":"W6943640815","doi":"10.15468/dl.rgxev5","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":[0.0008929184,0.001988819,0.00144167,0.004632582,0.0009230021,0.002331244,0.002534381,0.001868345,0.1594943],"category_scores_gemma":[0.005599513,0.0008762063,0.001177993,0.009392205,0.0004282417,0.002089696,0.002407526,0.001761418,0.2098375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443163,"about_ca_system_score_gemma":0.002255895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02092938,"about_ca_topic_score_gemma":0.03412404,"domain_scores_codex":[0.9990358,0.0001307457,0.0001216784,0.0003474179,0.0001988514,0.0001654004],"domain_scores_gemma":[0.9977424,0.0006561315,0.0002175992,0.0005728237,0.000551571,0.0002595777],"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":[0.00003355612,0.0000120401,0.0004184846,0.0005400006,0.00001456616,0.00001492214,0.00002158742,0.0001418175,0.0001319893,0.0003638219,0.9967939,0.00151319],"study_design_scores_gemma":[0.00007913791,0.00001098454,0.002008593,0.0001835537,0.00001536504,0.00003753346,0.00006934268,0.0001637508,0.0002090007,0.0007849372,0.9964191,0.00001869714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004831538,0.00002489576,0.00004042541,0.00003210717,0.0000122122,0.000004897158,0.9988647,0.0003552045,0.0006173749],"genre_scores_gemma":[0.0001656108,0.00003168708,0.0001886966,0.00004410864,0.000003416469,0.00003949961,0.9989169,0.0001405475,0.0004696498],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8405057,"threshold_uncertainty_score":0.5335616,"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."}}