{"id":"W6887011241","doi":"10.15468/dl.mhxwlz","title":"Occurrence Download","year":2016,"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); Range (aeronautics); Set (abstract data type); Download; Identification (biology)","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":[0.0008892115,0.002094876,0.001641305,0.005201383,0.0008718627,0.002584248,0.002878493,0.001866645,0.1445218],"category_scores_gemma":[0.005982717,0.0009173545,0.001167873,0.01071559,0.0004064332,0.002269235,0.002662462,0.001833815,0.2031436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001620805,"about_ca_system_score_gemma":0.002539395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02303142,"about_ca_topic_score_gemma":0.03938871,"domain_scores_codex":[0.9989483,0.0001364273,0.0001440388,0.0003646803,0.0002347046,0.0001717809],"domain_scores_gemma":[0.9976922,0.0006033824,0.0002604268,0.0005856094,0.0005849257,0.0002734418],"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":[0.00003185816,0.000009644846,0.0004263738,0.000593534,0.00001726606,0.00001452129,0.00002276336,0.0001273123,0.0001114701,0.0004252163,0.9967673,0.001452744],"study_design_scores_gemma":[0.00006662248,0.000007599907,0.00177096,0.0001899477,0.00001582432,0.00003594287,0.00005349853,0.0001328147,0.0001808926,0.0007791101,0.9967495,0.00001739591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003811872,0.00003051467,0.00003903,0.00002860348,0.00001003774,0.000003983536,0.9989359,0.00033305,0.000580713],"genre_scores_gemma":[0.0001464802,0.00003947963,0.0001632191,0.00003916455,0.000003016787,0.00003287078,0.9989772,0.0001300226,0.0004685249],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8554782,"threshold_uncertainty_score":0.4834735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734962626846364,"score_gpt":0.227796013577581,"score_spread":0.2104463873091174,"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."}}