{"id":"W6961866495","doi":"10.15468/dl.r3bh8d","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":"Download; Matching (statistics); Range (aeronautics); Identification (biology)","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":[0.0009971086,0.002034152,0.001666129,0.005257415,0.001006785,0.002692143,0.002852061,0.002084584,0.1618402],"category_scores_gemma":[0.005951142,0.0009382403,0.001158676,0.01026948,0.0004589604,0.002341911,0.002645927,0.002015073,0.218702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542931,"about_ca_system_score_gemma":0.002313253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02009596,"about_ca_topic_score_gemma":0.03450571,"domain_scores_codex":[0.9989645,0.0001420179,0.0001326271,0.0003632769,0.0002235788,0.0001740098],"domain_scores_gemma":[0.9975861,0.0006969548,0.0002326466,0.0006384419,0.0005511029,0.0002947437],"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":[0.00003084895,0.00001137264,0.0003866821,0.0006058286,0.00001611557,0.00001631602,0.0000256037,0.0001257066,0.000124578,0.0003847267,0.9969285,0.001343769],"study_design_scores_gemma":[0.00007657335,0.000007976327,0.001913695,0.0001934076,0.00001471788,0.00003966974,0.00007441127,0.000136212,0.0001817177,0.0007801802,0.9965634,0.00001805892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004042045,0.00002655013,0.00004212537,0.00003130094,0.000010786,0.000004822096,0.9988993,0.0003500791,0.0005945688],"genre_scores_gemma":[0.0001619081,0.00003269292,0.0001865694,0.00004284104,0.000003299315,0.00004110438,0.9989477,0.0001476844,0.0004361937],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8381598,"threshold_uncertainty_score":0.5414093,"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."}}