{"id":"W4385581977","doi":"10.1002/cjce.24459","title":"Issue Highlights","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009175505,0.00008787585,0.0001424811,0.0001280389,0.00009343818,0.0001358456,0.0006502803,0.00004311464,0.0006056234],"category_scores_gemma":[0.0005456802,0.00005871348,0.00004522774,0.0003066787,0.00008314273,0.0001101416,0.00002755715,0.0001842085,0.000514038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008502617,"about_ca_system_score_gemma":0.0002105087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007323548,"about_ca_topic_score_gemma":0.00005348366,"domain_scores_codex":[0.9990698,0.00002369821,0.0002426453,0.00008451918,0.0002354713,0.0003438335],"domain_scores_gemma":[0.9992638,0.0001106818,0.00008825239,0.0001583314,0.00006539107,0.0003135626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001835131,7.627096e-7,0.00002137662,0.00001003846,0.000002385786,0.00004697264,0.0002393459,0.03161816,0.9641845,0.0007736724,0.003050374,0.00005060263],"study_design_scores_gemma":[0.0001356682,0.00002231846,0.0003417546,0.00006959424,0.00001071095,0.0001947095,0.00001027899,0.01389272,0.9457987,0.0003892769,0.03897208,0.0001621971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940851,0.00005708793,0.0001524401,0.00377791,0.001626032,0.00003414662,0.000003247826,0.00004864549,0.000215351],"genre_scores_gemma":[0.9981815,9.11667e-7,0.001032855,0.00009219695,0.0005192261,0.00000117807,5.514423e-7,0.00001403561,0.0001575201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0359217,"threshold_uncertainty_score":0.6631151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007600256891794575,"score_gpt":0.212370181094072,"score_spread":0.2047699242022774,"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."}}