{"id":"W6906024521","doi":"10.15468/dl.ybdbcp","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); Alien; 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":[0.0009818957,0.001912265,0.001526771,0.004990498,0.0010452,0.002652816,0.002704811,0.002057622,0.1734479],"category_scores_gemma":[0.00636376,0.000875406,0.001246567,0.009411376,0.0004359162,0.002506194,0.002635413,0.001989129,0.2394471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001511072,"about_ca_system_score_gemma":0.002304354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02164019,"about_ca_topic_score_gemma":0.03446543,"domain_scores_codex":[0.9989586,0.0001480016,0.0001272031,0.0003688913,0.000226118,0.0001712182],"domain_scores_gemma":[0.9973142,0.0007893049,0.0002272201,0.0007076195,0.0006741426,0.0002876454],"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":[0.00002531579,0.00001077757,0.0003639183,0.0004565674,0.00001195834,0.00001419312,0.00002168194,0.0001040303,0.00009257992,0.0003282738,0.9971833,0.001387531],"study_design_scores_gemma":[0.00006370588,0.000008370549,0.001805263,0.0001970373,0.00001283836,0.00003578483,0.00008131632,0.0001559303,0.0001716629,0.0007622708,0.9966888,0.00001714432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004532347,0.0000280725,0.00004841763,0.0000444001,0.00001442705,0.000006175014,0.9986653,0.0004459858,0.000701854],"genre_scores_gemma":[0.0001708231,0.00003571724,0.0002146108,0.00005279723,0.000004425061,0.00004746834,0.9987607,0.0001711369,0.0005422022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8265521,"threshold_uncertainty_score":0.580241,"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."}}