{"id":"W6943547004","doi":"10.15468/dl.ue8swb","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Real world data; Set (abstract data type)","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":[0.0008684468,0.002446272,0.001670647,0.004241156,0.001059495,0.002384516,0.003315305,0.002315972,0.1042169],"category_scores_gemma":[0.004668531,0.0008076594,0.001268881,0.007544266,0.0004703251,0.00220255,0.002519723,0.002118329,0.1978967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001806163,"about_ca_system_score_gemma":0.00230437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02296024,"about_ca_topic_score_gemma":0.04349783,"domain_scores_codex":[0.9991031,0.0001150334,0.0001056457,0.0003117461,0.0002179826,0.0001466343],"domain_scores_gemma":[0.9983588,0.000400115,0.0001474066,0.0004581963,0.0004280388,0.0002073478],"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":[0.00003130615,0.00001337701,0.0003105917,0.0004333481,0.00001458935,0.00001756252,0.0000204446,0.0001258548,0.0001225638,0.0003310456,0.9969783,0.001601124],"study_design_scores_gemma":[0.00008556416,0.00001026444,0.001882108,0.0001771736,0.00001581978,0.00005874881,0.00007513794,0.0002727644,0.0002757373,0.0009659649,0.9961597,0.00002091759],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006737078,0.00004804131,0.00006970379,0.00004531376,0.00001601822,0.000007783465,0.9982838,0.0006811914,0.0007807072],"genre_scores_gemma":[0.0001670649,0.00003715253,0.000238852,0.00004184376,0.000003271838,0.00004591183,0.998902,0.0001292363,0.0004346812],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8957831,"threshold_uncertainty_score":0.3486402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0474189317061362,"score_gpt":0.2611006235048186,"score_spread":0.2136816917986823,"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."}}