{"id":"W6962206480","doi":"10.15468/dl.sd3h56","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":[0.0009262291,0.001817191,0.001481227,0.004940026,0.0009279842,0.002463552,0.002555784,0.001923465,0.1662113],"category_scores_gemma":[0.006137902,0.0008183519,0.001142392,0.009361385,0.0004138022,0.002199066,0.002416471,0.001803808,0.2276509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014491,"about_ca_system_score_gemma":0.002157146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02031286,"about_ca_topic_score_gemma":0.03156313,"domain_scores_codex":[0.999065,0.0001302281,0.0001195961,0.0003264291,0.0002002667,0.0001584313],"domain_scores_gemma":[0.9974566,0.0007664437,0.0002327593,0.0006382767,0.0006303649,0.0002755655],"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":[0.00002861696,0.00001083775,0.0004213029,0.0005536539,0.00001351826,0.00001572564,0.00002370261,0.0001221941,0.0001112223,0.0003409356,0.9968377,0.001520561],"study_design_scores_gemma":[0.00006970077,0.000009404975,0.001981676,0.0002202718,0.00001465164,0.00003819411,0.00008499544,0.0001641456,0.0001865323,0.0007181247,0.9964952,0.00001707788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004505054,0.00002681443,0.00004282083,0.00003747983,0.00001240035,0.000005549775,0.9988469,0.0003727924,0.0006102268],"genre_scores_gemma":[0.0001818654,0.00003598632,0.0001978588,0.00004781771,0.000004180396,0.00004611495,0.9988361,0.0001516749,0.0004983382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8337887,"threshold_uncertainty_score":0.5560323,"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."}}