{"id":"W6906131408","doi":"10.15468/dl.vsjn9c","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; Range (aeronautics); State (computer science); 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":[0.0008670697,0.002020105,0.001514846,0.005117819,0.0009933079,0.002471613,0.002810682,0.001903052,0.162128],"category_scores_gemma":[0.005311712,0.0009145879,0.001142371,0.01022915,0.000452262,0.002266363,0.002518383,0.001933138,0.2277823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001473474,"about_ca_system_score_gemma":0.002254225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01946559,"about_ca_topic_score_gemma":0.03507513,"domain_scores_codex":[0.998993,0.0001339831,0.0001245515,0.0003671616,0.000212255,0.0001691239],"domain_scores_gemma":[0.9977856,0.0005913123,0.0002161253,0.0005848114,0.0005549136,0.0002672902],"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":[0.00002983363,0.00001134006,0.0003725904,0.0004865175,0.0000133029,0.00001414309,0.00002070062,0.0001174706,0.0001144297,0.0003639702,0.9970157,0.001439911],"study_design_scores_gemma":[0.00006717625,0.000008762833,0.001731723,0.000164105,0.00001299092,0.00003660975,0.00006416424,0.0001305309,0.0001767082,0.000772444,0.9968177,0.0000170787],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004580539,0.00002674492,0.00003932632,0.00003140009,0.00001232198,0.000004643427,0.9988193,0.0003275879,0.0006927977],"genre_scores_gemma":[0.0001490854,0.00003179847,0.0001782769,0.00004258901,0.000003523587,0.00003640921,0.9989183,0.0001338193,0.0005062157],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.837872,"threshold_uncertainty_score":0.5423722,"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."}}