{"id":"W6943659769","doi":"10.15468/dl.wfynfz","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; Alien; Range (aeronautics); 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":[0.0009103497,0.002040362,0.001465906,0.004881765,0.0009489025,0.002431557,0.002543638,0.001917606,0.158222],"category_scores_gemma":[0.005873661,0.0008738788,0.001182656,0.009734978,0.0004394077,0.00204664,0.002473767,0.001751094,0.2182925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441489,"about_ca_system_score_gemma":0.002271064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02105812,"about_ca_topic_score_gemma":0.03393766,"domain_scores_codex":[0.9989918,0.0001378716,0.0001258985,0.000359925,0.0002115581,0.0001730012],"domain_scores_gemma":[0.9976339,0.0006795198,0.0002272596,0.0005984478,0.0005941333,0.0002667111],"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":[0.00003263694,0.00001202574,0.0004380016,0.0005340592,0.00001425417,0.00001473813,0.00002184307,0.0001376646,0.0001264088,0.0003536383,0.9968273,0.001487368],"study_design_scores_gemma":[0.00007905337,0.0000111859,0.002046178,0.0001885775,0.00001556671,0.00003715025,0.00007110629,0.0001671327,0.0002066257,0.0008083196,0.9963499,0.00001917384],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004859102,0.00002667354,0.00003941623,0.00003311272,0.00001223302,0.000005073915,0.9988353,0.0003724017,0.0006273327],"genre_scores_gemma":[0.0001706442,0.00003297452,0.0001876318,0.00004544525,0.000003694357,0.00004150416,0.9989051,0.0001437795,0.0004691107],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.841778,"threshold_uncertainty_score":0.5293053,"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."}}