{"id":"W4408843460","doi":"10.63132/ati.5.2025.cjicplru","title":"10.63132/ati.5.2025.CjICPlRU","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009876559,0.001060536,0.0008513762,0.003369153,0.001448983,0.005020173,0.00162662,0.003166053,0.9645447],"category_scores_gemma":[0.00234026,0.0006258908,0.000503782,0.002919655,0.0008399788,0.002425357,0.002770539,0.001467658,0.9713255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001713482,"about_ca_system_score_gemma":0.000998952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006329659,"about_ca_topic_score_gemma":0.006329084,"domain_scores_codex":[0.9995304,0.00004937154,0.0000380611,0.0001062522,0.0001790193,0.00009698271],"domain_scores_gemma":[0.9983497,0.0002164101,0.00008058645,0.0003881168,0.0004196299,0.0005455783],"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":[0.0000826768,0.0001219228,0.0004612028,0.0001508231,0.000006475815,0.00007976804,0.00004130615,0.0002288235,0.0007151329,0.007116387,0.6874607,0.3035348],"study_design_scores_gemma":[0.00002249873,0.00001933056,0.0005713807,0.0001171612,0.000004943305,0.00009028472,0.00003817165,0.0003755159,0.0003957493,0.00152122,0.9968318,0.00001200406],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003083448,0.0002150097,0.001282905,0.0006199491,0.0003688395,0.00005725627,0.002811575,0.003741107,0.9905951],"genre_scores_gemma":[0.00259304,0.0001901678,0.0006736265,0.0004392142,0.0001117292,0.00003714489,0.002185003,0.0009849586,0.9927852],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03545529,"threshold_uncertainty_score":0.05057269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157102062610088,"score_gpt":0.1607189375930548,"score_spread":0.1391479169669539,"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."}}