{"id":"W6924685603","doi":"10.15468/dl.x7sekw","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); Data set; Real world data","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":[0.0009944129,0.002094611,0.001640495,0.005424761,0.0009917869,0.002665664,0.002797459,0.002002084,0.1648913],"category_scores_gemma":[0.005654748,0.0009239787,0.001232084,0.01076035,0.0004502462,0.002188085,0.002756876,0.001876983,0.2346845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514931,"about_ca_system_score_gemma":0.002348061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0212177,"about_ca_topic_score_gemma":0.03560767,"domain_scores_codex":[0.9988813,0.00014415,0.0001412805,0.0003801968,0.0002570314,0.0001960085],"domain_scores_gemma":[0.9976114,0.000615294,0.0002294605,0.0006499363,0.0006008711,0.0002930197],"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":[0.00003604187,0.00001175248,0.000399164,0.0006096368,0.00001751352,0.00001617106,0.00002416192,0.0001277493,0.0001477819,0.0003913127,0.9966905,0.001528167],"study_design_scores_gemma":[0.00007382758,0.000008672586,0.001913256,0.0001895233,0.0000151633,0.00003678456,0.00006353856,0.000129441,0.0002088376,0.0007452805,0.9965979,0.00001771049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004162823,0.00002810259,0.00004021267,0.00002915012,0.00001048565,0.000004926938,0.9988143,0.0003922391,0.0006389783],"genre_scores_gemma":[0.0001446438,0.00003145987,0.0001621436,0.0000402376,0.000003178638,0.00003508799,0.9990257,0.000145439,0.00041211],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8351086,"threshold_uncertainty_score":0.5516164,"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."}}