{"id":"W3204771300","doi":"","title":"Explaining the Selection of Routines for Change during Organizational Search","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Management and Organizational Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Organizational change; Knowledge management; Computer science; Political science; Artificial intelligence; Public relations","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002837812,0.0003225595,0.0002772236,0.001262775,0.0009784796,0.004749525,0.001197704,0.002497185,0.01439073],"category_scores_gemma":[0.03248386,0.0004157141,0.0006758419,0.001251606,0.002620537,0.004681254,0.001471403,0.001352359,0.001342927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001390425,"about_ca_system_score_gemma":0.001280594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006299587,"about_ca_topic_score_gemma":0.005010225,"domain_scores_codex":[0.9977647,0.001246067,0.0001095556,0.0003576405,0.0002549932,0.0002669955],"domain_scores_gemma":[0.9785327,0.01488044,0.002234364,0.002434569,0.001124093,0.0007938888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00102286,0.0002966576,0.09492543,0.0005377833,0.00009654024,0.001290615,0.05667341,0.01439256,0.01117081,0.6862528,0.007280716,0.1260598],"study_design_scores_gemma":[0.0002058627,0.0004779856,0.1622168,0.0006107532,0.0001250139,0.001225888,0.0350359,0.2099067,0.006520137,0.535592,0.04784332,0.0002396644],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7459049,0.0005441111,0.1579475,0.004042,0.000106634,0.000329155,0.0003712265,0.0007841246,0.08997037],"genre_scores_gemma":[0.9779208,0.00007845787,0.01756024,0.00006787736,0.00001631543,0.00005897793,0.0002131423,0.0001304603,0.003953678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01439073,"threshold_uncertainty_score":0.04814184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02255872149244236,"score_gpt":0.2174306482113519,"score_spread":0.1948719267189095,"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."}}