{"id":"W6924556843","doi":"10.15468/dl.mj1gcv","title":"Occurrence Download","year":2016,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Download; 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":[0.0009013759,0.002260817,0.001575835,0.005106132,0.0009008818,0.002606638,0.002938906,0.00195484,0.1205719],"category_scores_gemma":[0.005394657,0.0008738746,0.001222577,0.009975161,0.0004258866,0.002293755,0.002510447,0.001984564,0.1894149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001683589,"about_ca_system_score_gemma":0.002503038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02302718,"about_ca_topic_score_gemma":0.03948706,"domain_scores_codex":[0.9989237,0.0001442398,0.0001406177,0.0003724979,0.0002476588,0.0001711355],"domain_scores_gemma":[0.9979241,0.0005359207,0.0002210731,0.0005356828,0.0005354499,0.0002477491],"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":[0.00003358058,0.00001199317,0.0004562653,0.0005076011,0.00001676197,0.00001670425,0.00002207917,0.0001622462,0.0001113616,0.0004699259,0.9966514,0.001540166],"study_design_scores_gemma":[0.00006647809,0.000007843345,0.001695152,0.0001675681,0.00001419305,0.00003814866,0.00005545084,0.0001837256,0.0001901951,0.0009066972,0.9966573,0.00001724984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004819962,0.00003245733,0.00004726442,0.00003353561,0.00001153386,0.00000454276,0.9987366,0.0004156459,0.0006701826],"genre_scores_gemma":[0.0001512873,0.00003719693,0.0001796671,0.00003902177,0.000003092087,0.00003096302,0.9989499,0.0001304324,0.0004784836],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8794281,"threshold_uncertainty_score":0.4033532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007808726010512496,"score_gpt":0.1805010812832617,"score_spread":0.1726923552727492,"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."}}