{"id":"W6943344080","doi":"10.15468/dl.w3j5f7","title":"Occurrence Download","year":2023,"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); Identification (biology); 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":[0.0008239626,0.001897005,0.00161036,0.005232208,0.001134851,0.002693388,0.002782759,0.002180461,0.1642579],"category_scores_gemma":[0.005749499,0.0009056394,0.00137361,0.009977478,0.0004434116,0.002492052,0.002646338,0.002008654,0.2359518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001534482,"about_ca_system_score_gemma":0.002350508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01939632,"about_ca_topic_score_gemma":0.03249734,"domain_scores_codex":[0.9989932,0.0001280865,0.0001304698,0.0003679682,0.0002098218,0.0001703815],"domain_scores_gemma":[0.9978206,0.0005969611,0.0001867331,0.0005755149,0.000574221,0.0002459537],"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":[0.00002994234,0.00001166152,0.0004587706,0.0006596066,0.00001589669,0.00001878102,0.00002581509,0.0001242665,0.0001387667,0.0003712659,0.9962866,0.001858626],"study_design_scores_gemma":[0.00006313573,0.000008686527,0.00183522,0.0002109844,0.00001547317,0.00004681163,0.00007580957,0.0001716436,0.0001911787,0.0007122139,0.9966522,0.00001660672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000611918,0.00004610172,0.00005631901,0.00004709508,0.00001673344,0.00000670832,0.9983999,0.0005231226,0.0008428362],"genre_scores_gemma":[0.0001888719,0.00004667183,0.000222781,0.00005753657,0.000004464796,0.00004426844,0.9987167,0.0001649494,0.0005537701],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8357421,"threshold_uncertainty_score":0.5494976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}