{"id":"W6943582445","doi":"10.15468/dl.vsevl8","title":"Occurrence Download","year":2019,"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; Matching (statistics); Range (aeronautics); Feature (linguistics); China","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":[0.0007709383,0.003061724,0.002262547,0.008057082,0.001239918,0.0035846,0.002295828,0.002593696,0.2512741],"category_scores_gemma":[0.006116305,0.0009881406,0.002065796,0.01178155,0.0004165819,0.003562397,0.003454934,0.00206216,0.3087056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001419132,"about_ca_system_score_gemma":0.002940207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02391839,"about_ca_topic_score_gemma":0.0365922,"domain_scores_codex":[0.9987667,0.00014213,0.0001954768,0.0004201506,0.0002564031,0.0002191367],"domain_scores_gemma":[0.9975736,0.0007318037,0.0001995795,0.0005602958,0.0005863142,0.0003485182],"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":[0.00006351442,0.00002207602,0.0004321667,0.0009572319,0.00002185008,0.00003590588,0.00004146002,0.000210462,0.0001391517,0.0005549845,0.9932218,0.004299454],"study_design_scores_gemma":[0.00009176504,0.00001571362,0.001440917,0.0002579216,0.00002209518,0.00006552012,0.0001163176,0.0004199453,0.0001859574,0.001375622,0.9959806,0.00002758386],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009774125,0.0001051479,0.0001307773,0.00007510581,0.00004023434,0.00001590066,0.9958069,0.001768101,0.001959976],"genre_scores_gemma":[0.0003255224,0.0001257981,0.0006552823,0.0001043795,0.00001139074,0.00006527171,0.9970685,0.0003930254,0.001250894],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7487259,"threshold_uncertainty_score":0.8405955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}