{"id":"W1988139019","doi":"10.1016/j.ijpe.2006.02.013","title":"Using the learning curve to maximize IT productivity: A decision analysis model for timing software upgrades","year":2006,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Learning curve; Productivity; Upgrade; Computer science; Software; Vendor; Software development; Business; Marketing; Economics; Operating system","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":[0.0008092973,0.0001309611,0.0002313296,0.0006159223,0.0001665433,0.0009372345,0.0003343378,0.00003564593,0.00001272621],"category_scores_gemma":[0.0005281061,0.0001089174,0.000257532,0.0001991226,0.00002618188,0.004097891,0.00009875198,0.0001214351,0.000009648715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888608,"about_ca_system_score_gemma":0.00004538907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005824937,"about_ca_topic_score_gemma":0.0001716057,"domain_scores_codex":[0.9988813,0.000001756677,0.0005979144,0.0002339503,0.0001271361,0.0001579881],"domain_scores_gemma":[0.99841,0.00005440591,0.0008020165,0.0001279879,0.000592437,0.00001316227],"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":[0.0001639916,0.00004882359,0.005475701,0.000005645896,0.0002155592,5.897073e-7,0.00004102376,0.9789424,0.0000561995,0.00286784,0.0009770225,0.01120519],"study_design_scores_gemma":[0.0004076005,0.00001405762,0.00107611,0.00003323421,0.0002790082,0.00003462335,0.0003718275,0.9119147,0.0001528914,0.06373868,0.02174346,0.0002338215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7303786,0.0000144468,0.2659432,0.002143004,0.001209319,0.0001352724,0.000003630586,0.00001249314,0.0001600039],"genre_scores_gemma":[0.9767802,0.000008660149,0.0183227,0.0003741786,0.004046664,0.000005349001,0.00001809333,0.00002331456,0.0004208224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2476205,"threshold_uncertainty_score":0.9037774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06354984025068575,"score_gpt":0.2824998759180996,"score_spread":0.2189500356674139,"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."}}