{"id":"W4404378603","doi":"10.1080/00207543.2024.2426694","title":"A model for scheduling the resource deployment in a multi-stage ramp-up production system","year":2024,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Process Optimization and Integration","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Software deployment; Scheduling (production processes); Production (economics); Computer science; Integrated production; Operations research; Production model; Resource (disambiguation); Industrial engineering; Engineering; Operations management; Economics; Microeconomics; Software engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002821424,0.000091465,0.0001019621,0.0007383086,0.00008353723,0.0002316289,0.0003093791,0.00005328047,0.000008373934],"category_scores_gemma":[0.0007981242,0.00006729101,0.00007076131,0.0004186861,0.0000440945,0.0005196332,0.00002672069,0.0005384258,0.000007749513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006491212,"about_ca_system_score_gemma":0.0001675188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006757078,"about_ca_topic_score_gemma":0.00002887041,"domain_scores_codex":[0.9983525,0.0000818588,0.0004706807,0.0001858603,0.0007338879,0.0001752516],"domain_scores_gemma":[0.9984863,0.00007094625,0.00006073887,0.0001197652,0.001222169,0.00004009307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000104637,0.00003588095,0.00001800032,0.0001641211,0.00007097027,0.000004568229,0.001537126,0.9768429,0.009023414,0.002358735,0.003440232,0.006399391],"study_design_scores_gemma":[0.0002349964,0.00002455179,0.00001244618,0.0004103866,0.000005934009,0.00007094644,0.001487527,0.9761038,0.01134326,0.0001275518,0.01011597,0.00006255799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07197643,0.002370547,0.9054496,0.01176157,0.006974059,0.0009277477,0.00001257299,0.0001972487,0.0003302391],"genre_scores_gemma":[0.9895375,0.0002524697,0.006206371,0.0000140212,0.0009382365,0.00009394755,0.000007437434,0.00003185801,0.0029181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9175611,"threshold_uncertainty_score":0.2744048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1998995204484082,"score_gpt":0.423589050643901,"score_spread":0.2236895301954927,"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."}}