{"id":"W6962078708","doi":"10.15468/dl.n2sc5c","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); Species name; State (computer science)","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":[0.0009971358,0.001949263,0.001603359,0.005143813,0.001023114,0.002580052,0.002833851,0.002031431,0.160821],"category_scores_gemma":[0.005780528,0.0009273686,0.001118318,0.009997379,0.0004689617,0.002290178,0.002607274,0.00206432,0.2241787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542511,"about_ca_system_score_gemma":0.002333464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0195744,"about_ca_topic_score_gemma":0.03381333,"domain_scores_codex":[0.9989994,0.000138107,0.000126005,0.000350501,0.000218473,0.0001674886],"domain_scores_gemma":[0.9976419,0.000666131,0.0002292665,0.0006133153,0.0005589046,0.0002903601],"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":[0.00002906607,0.00001168779,0.0003591785,0.000540107,0.00001405662,0.00001548219,0.00002474343,0.0001188343,0.0001214391,0.0004008429,0.997029,0.001335495],"study_design_scores_gemma":[0.00007302279,0.000007629844,0.001665982,0.0001805607,0.00001307779,0.00003581908,0.0000764701,0.0001265816,0.0001792123,0.000771817,0.9968525,0.00001732398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004296008,0.00002690151,0.00004371133,0.00003378462,0.00001175603,0.000005208618,0.998854,0.0003388537,0.0006428346],"genre_scores_gemma":[0.0001624864,0.00003302037,0.0002015024,0.00004391886,0.000003493676,0.00004351167,0.9988983,0.0001435886,0.0004702],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.839179,"threshold_uncertainty_score":0.5379999,"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."}}