{"id":"W1528550101","doi":"10.1111/1467-8551.12060","title":"Digitalization and Promotion: An Empirical Study in a Large Law Firm","year":2014,"lang":"en","type":"article","venue":"British Journal of Management","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University; Université Laval","funders":"","keywords":"Bespoke; Promotion (chess); Context (archaeology); Work (physics); Service (business); Empirical research; Marketing; Law; Business; Economics; Public relations; Political science; Politics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002136969,0.0002908036,0.0004545191,0.002185537,0.004453905,0.003666841,0.001321918,0.001309103,0.005024658],"category_scores_gemma":[0.006773417,0.0006208074,0.0002068577,0.003111871,0.00231576,0.002673859,0.002870527,0.002905387,0.0009343913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002544341,"about_ca_system_score_gemma":0.002165896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04709848,"about_ca_topic_score_gemma":0.07682648,"domain_scores_codex":[0.9983713,0.0005795654,0.00006535275,0.0002440207,0.0002712762,0.0004685355],"domain_scores_gemma":[0.9813753,0.008040433,0.004810571,0.0005067699,0.0008647561,0.004402085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002195514,0.006427504,0.9466251,0.00004959938,0.00002803619,0.001348704,0.03205804,0.0001538929,0.0004247209,0.0004364802,0.0007619642,0.01146644],"study_design_scores_gemma":[0.00003928061,0.0009524763,0.9119267,0.00004977454,0.0000253272,0.0003950081,0.08382775,0.0007163261,0.0001786286,0.0001112977,0.001751461,0.00002598292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993,0.00005282267,0.00002964553,0.00009926897,0.000001273934,0.00001481479,0.00003330372,0.00000112156,0.0004676844],"genre_scores_gemma":[0.9988443,0.0001327728,0.00009834334,0.0001269779,0.00001154617,0.00001940855,0.00008159078,0.000002223439,0.0006828907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04709848,"threshold_uncertainty_score":0.09364867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05131590171850688,"score_gpt":0.3723395546789029,"score_spread":0.321023652960396,"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."}}