{"id":"W6906132082","doi":"10.15468/dl.scnsk2","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); Download; Range (aeronautics); 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":[0.0009323251,0.002006968,0.001586762,0.004875806,0.0009632834,0.002558156,0.002665134,0.001898512,0.1701027],"category_scores_gemma":[0.005656705,0.0009578692,0.001139879,0.009913048,0.0004133021,0.002329914,0.002506453,0.001882218,0.226491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530814,"about_ca_system_score_gemma":0.002250815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02042819,"about_ca_topic_score_gemma":0.03447818,"domain_scores_codex":[0.9989523,0.0001423443,0.0001340115,0.0003728099,0.000221809,0.0001767421],"domain_scores_gemma":[0.9975656,0.0006557754,0.000238179,0.0006321045,0.0006328276,0.0002755089],"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":[0.0000329704,0.00001121739,0.000362512,0.0005505237,0.00001445744,0.00001330709,0.00002006882,0.0001163204,0.0001193355,0.000383392,0.9969597,0.001416211],"study_design_scores_gemma":[0.00007174748,0.000008688423,0.001781143,0.0001816713,0.00001384043,0.00003221089,0.00005747022,0.0001238401,0.000181676,0.0007633911,0.9967662,0.0000181285],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003740279,0.00002474712,0.00003757293,0.00002943182,0.00001040623,0.000004528184,0.9989244,0.000311776,0.0006196937],"genre_scores_gemma":[0.0001476095,0.00003387343,0.0001826858,0.0000451948,0.000003490178,0.00003923351,0.9989016,0.0001369545,0.0005093561],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8298973,"threshold_uncertainty_score":0.5690503,"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."}}