{"id":"W6931376771","doi":"10.5281/zenodo.5014246","title":"CINECA synthetic cohort NA Canada CHILD [CC-BY-NC-SA]","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Environmental Monitoring and Data Management","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Population; Circumstantial evidence; Identification (biology); Term (time); Selection (genetic algorithm)","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":[],"consensus_categories":[],"category_scores_codex":[0.003325832,0.00155759,0.001906332,0.001961862,0.002269276,0.004321761,0.005133924,0.002561909,0.2679865],"category_scores_gemma":[0.02179658,0.001325299,0.002324679,0.004646693,0.0009561263,0.001703291,0.00325768,0.002380026,0.1409848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00382508,"about_ca_system_score_gemma":0.0138093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2583166,"about_ca_topic_score_gemma":0.3789667,"domain_scores_codex":[0.9976814,0.0003667596,0.0001313918,0.000765114,0.0006511763,0.0004041152],"domain_scores_gemma":[0.9923124,0.001758728,0.000493826,0.002333821,0.002296984,0.0008041589],"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":[0.00004625265,0.000006208936,0.0005202848,0.0001417519,0.00002354107,0.00001696182,0.00002534327,0.0001662342,0.00006891236,0.0005501539,0.9970433,0.001391132],"study_design_scores_gemma":[0.0004715321,0.00001394107,0.003650601,0.0003717891,0.00003859877,0.000122892,0.00007143253,0.001482129,0.0003495781,0.002254614,0.9911026,0.00007023378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002377385,0.00004627219,0.0006283453,0.0003286945,0.0001832836,0.00004926528,0.9947535,0.001760391,0.002012466],"genre_scores_gemma":[0.001562131,0.00008304737,0.002506641,0.0004090274,0.00004443447,0.0003940394,0.9911557,0.001548531,0.002296349],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7416834,"threshold_uncertainty_score":0.896504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101267621644638,"score_gpt":0.1786111360909106,"score_spread":0.1675984598744642,"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."}}