{"id":"W6961863228","doi":"10.15468/dl.kjq2gy","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":[0.0009984776,0.002009959,0.001636361,0.004860097,0.001035768,0.002592397,0.002917805,0.002185054,0.1531298],"category_scores_gemma":[0.005740999,0.0009156527,0.001183249,0.009450674,0.0004730986,0.002399535,0.002593219,0.002121082,0.2195681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001547009,"about_ca_system_score_gemma":0.002327386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02009798,"about_ca_topic_score_gemma":0.03586188,"domain_scores_codex":[0.9989676,0.0001477822,0.0001273988,0.00036694,0.00022142,0.0001687858],"domain_scores_gemma":[0.9975609,0.0006770654,0.0002296203,0.0006645196,0.0005800193,0.0002879106],"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":[0.00002937962,0.00001248585,0.0003688106,0.0005136022,0.00001396534,0.00001482672,0.00002360941,0.000126251,0.0001132457,0.0003815712,0.9970898,0.00131245],"study_design_scores_gemma":[0.00007574264,0.000008090718,0.001698322,0.0001773892,0.00001295436,0.00003511199,0.00007553072,0.0001413223,0.0001790331,0.0008200022,0.9967585,0.00001795689],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000419071,0.00002592164,0.00004355447,0.0000354247,0.00001208902,0.000005210016,0.9988772,0.0003453481,0.0006133519],"genre_scores_gemma":[0.0001561153,0.00003138265,0.0002041572,0.00004425677,0.000003514508,0.00004188292,0.9989209,0.000136539,0.000461269],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8468702,"threshold_uncertainty_score":0.5122702,"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."}}