{"id":"W6961990695","doi":"10.15468/dl.3gzq8p","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Data set; Set (abstract data type)","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":[0.0007915568,0.001797822,0.001396025,0.00434834,0.0007676135,0.002105894,0.002376145,0.001809269,0.1190239],"category_scores_gemma":[0.004678668,0.0007481898,0.001115964,0.008206053,0.0003931145,0.001691072,0.002070784,0.001631215,0.16602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504711,"about_ca_system_score_gemma":0.002098825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02401185,"about_ca_topic_score_gemma":0.0421653,"domain_scores_codex":[0.999189,0.0001118193,0.000105657,0.0002768759,0.0001767558,0.0001399629],"domain_scores_gemma":[0.9982311,0.0004788336,0.0001859336,0.0004351466,0.0004393783,0.0002296731],"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":[0.00003828548,0.00001225979,0.0005910731,0.0006661089,0.00002208027,0.0000192661,0.00002259195,0.0001918057,0.0001570645,0.0003905797,0.9960776,0.001811286],"study_design_scores_gemma":[0.00008615687,0.00001061948,0.002660454,0.0002100969,0.00001893681,0.00004655911,0.00006822008,0.0002080419,0.0002374944,0.0007541293,0.9956815,0.00001774945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005300524,0.00003432293,0.00003966299,0.00003148172,0.00001015409,0.000004981088,0.9988989,0.0003524565,0.0005750768],"genre_scores_gemma":[0.0001946709,0.00003687145,0.0001672836,0.00004334723,0.000003120149,0.00002894535,0.9990466,0.00009278858,0.0003862833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8809761,"threshold_uncertainty_score":0.3981748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01413458325980542,"score_gpt":0.2425308487059663,"score_spread":0.2283962654461609,"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."}}