{"id":"W6887149346","doi":"10.15468/dl.w9urrx","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":"Matching (statistics); Range (aeronautics); Download; Set (abstract data type); 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":[0.0009394251,0.001968368,0.001568412,0.005042387,0.001063085,0.002469283,0.002831038,0.00194161,0.1647433],"category_scores_gemma":[0.005797959,0.00091657,0.001145979,0.01015785,0.0004410019,0.002361509,0.002650632,0.001905162,0.2237534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584119,"about_ca_system_score_gemma":0.002336108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02134932,"about_ca_topic_score_gemma":0.03855662,"domain_scores_codex":[0.9989288,0.0001398178,0.0001343234,0.0003829318,0.0002318,0.0001822697],"domain_scores_gemma":[0.997703,0.0006024244,0.0002190132,0.000576109,0.0006256402,0.0002739509],"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":[0.00002940785,0.000010679,0.000357045,0.000523496,0.00001321081,0.00001423421,0.00002084621,0.0001054042,0.0001188323,0.0003669297,0.9971004,0.001339564],"study_design_scores_gemma":[0.00006544054,0.000008319585,0.001707188,0.0001732008,0.00001298656,0.00003506004,0.00006225507,0.0001146083,0.0001706159,0.0007338378,0.996899,0.00001754323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004354325,0.00002733393,0.00004218425,0.00003368268,0.00001248852,0.00000497037,0.9987885,0.0003300967,0.000717162],"genre_scores_gemma":[0.0001452369,0.00003252305,0.0001844432,0.00004567776,0.000003421016,0.00004044537,0.9988938,0.0001437238,0.000510818],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8352567,"threshold_uncertainty_score":0.5511212,"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."}}