{"id":"W6887054526","doi":"10.15468/dl.r5sxm2","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":[0.0009075237,0.001986996,0.001454061,0.004758132,0.0009388618,0.002397119,0.002570153,0.001852754,0.1634103],"category_scores_gemma":[0.005772368,0.000898702,0.001176144,0.009631346,0.0004314912,0.002170818,0.00248429,0.001798468,0.2157192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001440079,"about_ca_system_score_gemma":0.00226021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02028617,"about_ca_topic_score_gemma":0.03280865,"domain_scores_codex":[0.9990114,0.0001327429,0.0001250987,0.0003554634,0.0002062163,0.000169058],"domain_scores_gemma":[0.9976667,0.0006681486,0.0002225128,0.0006082057,0.0005665469,0.0002678501],"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":[0.00003112674,0.00001121833,0.0003905092,0.0004980948,0.00001374316,0.00001403765,0.00002070338,0.000131578,0.0001206594,0.0003615984,0.996935,0.001471673],"study_design_scores_gemma":[0.00007506591,0.00001022659,0.001906108,0.0001768679,0.00001455367,0.0000364258,0.00006628556,0.0001557871,0.0001977971,0.0007971434,0.9965459,0.00001799866],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004708401,0.00002473536,0.00004144847,0.00003325222,0.00001252968,0.000004987508,0.9988146,0.0003766224,0.0006447738],"genre_scores_gemma":[0.0001656704,0.00003285598,0.0001905697,0.00004596051,0.000003620891,0.00004085014,0.9988764,0.0001539284,0.0004902015],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8365897,"threshold_uncertainty_score":0.546662,"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."}}