{"id":"W6924825001","doi":"10.15468/dl.s8tzru","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Adhesion, Friction, and Surface Interactions","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); State (computer science); Confidentiality","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":[0.0008691301,0.002285826,0.001658769,0.004044192,0.001045817,0.002488843,0.003276847,0.00264771,0.09529102],"category_scores_gemma":[0.004004623,0.0008555586,0.001375008,0.007408892,0.0005060344,0.001894958,0.002412669,0.002116368,0.1634108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001612659,"about_ca_system_score_gemma":0.001988324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02247444,"about_ca_topic_score_gemma":0.03927611,"domain_scores_codex":[0.9991593,0.0001067599,0.0000960336,0.0002954276,0.0002013078,0.000141207],"domain_scores_gemma":[0.9983283,0.0004444088,0.0001522019,0.0004830641,0.0003938843,0.0001980847],"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":[0.00003749804,0.00002259385,0.0006602903,0.000693222,0.00002068119,0.00002229615,0.00002882828,0.0003092547,0.0001775741,0.0005069219,0.9954512,0.002069644],"study_design_scores_gemma":[0.00008303776,0.00001164982,0.002575699,0.0002126965,0.00001647589,0.00004730375,0.0000838106,0.0003218622,0.0002535548,0.000937178,0.9954352,0.00002160574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000775058,0.00004347992,0.00006288006,0.00003571616,0.0000141264,0.000006154139,0.9986684,0.0004530107,0.0006387205],"genre_scores_gemma":[0.0001960779,0.00003803755,0.0002258943,0.00003624781,0.000002860513,0.0000392499,0.9989663,0.00009108189,0.0004042088],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.904709,"threshold_uncertainty_score":0.3187802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111492521145738,"score_gpt":0.203274190701331,"score_spread":0.1921592654898736,"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."}}