{"id":"W6924871257","doi":"10.15468/dl.x7qzpv","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","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":[0.0009237794,0.002140788,0.001598889,0.005056416,0.001011953,0.002531817,0.002915925,0.002215373,0.1302938],"category_scores_gemma":[0.005960216,0.0008538516,0.00131251,0.009122875,0.0004348087,0.002266253,0.00230113,0.002054754,0.1977902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001601531,"about_ca_system_score_gemma":0.002186905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01827038,"about_ca_topic_score_gemma":0.02998215,"domain_scores_codex":[0.9989856,0.0001427736,0.0001306526,0.0003620327,0.0002182859,0.0001607165],"domain_scores_gemma":[0.9977976,0.0006532258,0.000191981,0.0005705394,0.0005472239,0.0002394416],"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":[0.00003122644,0.00001375819,0.0003919488,0.0005957494,0.00001578265,0.0000172989,0.00001960311,0.000151305,0.0001130752,0.0003487686,0.9967763,0.001525123],"study_design_scores_gemma":[0.00008833449,0.00001053353,0.001832686,0.0002095905,0.00001684315,0.00004806535,0.00007422757,0.0002435184,0.0002114668,0.0008543007,0.9963924,0.00001800475],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005396188,0.00004009231,0.00005014848,0.00004349104,0.00001371116,0.0000069928,0.998738,0.0004341549,0.0006195828],"genre_scores_gemma":[0.0001788776,0.00004169333,0.0002145989,0.00005002732,0.000003900327,0.00004896174,0.9988978,0.0001273565,0.000436736],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8697062,"threshold_uncertainty_score":0.4358761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169086788684483,"score_gpt":0.2209328989132924,"score_spread":0.2040242200448441,"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."}}