{"id":"W6905848323","doi":"10.15468/dl.pkjbw3","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":[0.0009198678,0.002052762,0.001548936,0.00491227,0.000941128,0.002468333,0.002632367,0.001950374,0.1687174],"category_scores_gemma":[0.005981673,0.0009057123,0.001179162,0.009747618,0.0004422183,0.002069729,0.002478142,0.001806993,0.2239329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510708,"about_ca_system_score_gemma":0.002304029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02151611,"about_ca_topic_score_gemma":0.03457922,"domain_scores_codex":[0.9990311,0.00013124,0.0001215294,0.0003504603,0.0002021731,0.0001636018],"domain_scores_gemma":[0.9976761,0.0006847865,0.0002242774,0.0005785763,0.0005782283,0.0002580716],"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":[0.00003045523,0.00001105382,0.0003810366,0.0005567776,0.00001426779,0.00001413384,0.00002204822,0.0001291446,0.0001135923,0.0003338634,0.9969512,0.001442406],"study_design_scores_gemma":[0.00008259735,0.00001039534,0.001887823,0.0001940624,0.00001539054,0.00003545979,0.00007017365,0.0001638014,0.0001886339,0.0007703643,0.9965625,0.00001866034],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000419499,0.00002580385,0.00003869382,0.00003295573,0.00001161179,0.00000528874,0.9988967,0.0003634248,0.0005834611],"genre_scores_gemma":[0.0001676544,0.00003487348,0.0002028959,0.00004766358,0.000003776882,0.00004826808,0.998835,0.0001573574,0.0005024974],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8312826,"threshold_uncertainty_score":0.5644159,"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."}}