{"id":"W2013425394","doi":"10.1016/s0925-5273(03)00084-7","title":"Countering forgetting through training and deployment","year":2003,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Forgetting; Software deployment; Flexibility (engineering); Task (project management); Computer science; Context (archaeology); Similarity (geometry); Productivity; Artificial intelligence; Cognitive psychology; Psychology; Economics; Software engineering; Management","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":[0.0002552336,0.00006321901,0.00009021681,0.00007697068,0.00002635293,0.00005689335,0.00006916458,0.00002343858,0.00001805263],"category_scores_gemma":[0.0001005473,0.00006813002,0.00003026823,0.00002450161,0.00001439282,0.0003890113,0.000006163847,0.00009284194,0.000001782177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009548523,"about_ca_system_score_gemma":0.00002121393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.417968e-7,"about_ca_topic_score_gemma":8.869558e-7,"domain_scores_codex":[0.9994949,0.000008556491,0.0002929465,0.00006904416,0.00006288847,0.00007172133],"domain_scores_gemma":[0.9996884,0.00001519205,0.0001103976,0.00004038949,0.0001159733,0.00002963335],"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":[0.000009188036,0.00001702149,0.0006899053,0.000008142159,0.0002046459,0.000002885559,0.001967868,0.9699122,0.0005880503,0.002724332,0.0001752351,0.02370048],"study_design_scores_gemma":[0.005086479,0.0002661755,0.00128441,0.0004976782,0.0001545266,0.009307718,0.0142634,0.5221152,0.1267956,0.01966373,0.2990263,0.001538788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8781089,0.0005332626,0.1074605,0.0007087641,0.01147596,0.00005091595,0.000002124931,0.00005353416,0.001606134],"genre_scores_gemma":[0.9010873,0.0007776331,0.09723868,0.00006821437,0.0007648894,0.000001161146,9.651718e-7,0.00001800248,0.00004312748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.447797,"threshold_uncertainty_score":0.2778262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02265905760632428,"score_gpt":0.2391113325444366,"score_spread":0.2164522749381123,"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."}}