{"id":"W6887091325","doi":"10.15468/dl.naea7m","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); State (computer science); Data set","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":[0.001001453,0.001986194,0.001662031,0.005021693,0.0009872364,0.002669416,0.002839335,0.002031819,0.1727052],"category_scores_gemma":[0.005915649,0.0009466485,0.001152578,0.0102653,0.0004493202,0.002419681,0.002648927,0.001991704,0.2407553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548447,"about_ca_system_score_gemma":0.002236116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01938294,"about_ca_topic_score_gemma":0.03303669,"domain_scores_codex":[0.9989849,0.0001363227,0.0001277266,0.0003589237,0.0002233468,0.0001687718],"domain_scores_gemma":[0.9976351,0.0006631136,0.0002229788,0.0006236271,0.0005799831,0.0002750749],"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":[0.00002799931,0.00001038003,0.0003487392,0.0005527359,0.00001433315,0.0000142807,0.00002349577,0.000116858,0.0001139109,0.0003860349,0.9970472,0.001343962],"study_design_scores_gemma":[0.00006779085,0.000006885266,0.001621315,0.0001837876,0.00001295658,0.00003215712,0.000066897,0.0001275489,0.0001764301,0.0007784266,0.996909,0.00001684883],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003545482,0.00002418201,0.00004174234,0.00003020728,0.00001061131,0.000004696864,0.998889,0.0003305089,0.000633492],"genre_scores_gemma":[0.0001513883,0.00003279751,0.0001935523,0.00004359329,0.000003446588,0.00004270021,0.9988822,0.0001609839,0.0004893846],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8272948,"threshold_uncertainty_score":0.5777564,"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."}}