{"id":"W3131046376","doi":"10.20381/ruor-24861","title":"Evaluating the correlation between Innovation in HR practices and organizational performance using Shapley Value","year":2020,"lang":"en","type":"article","venue":"uO Research (University of Ottawa)","topic":"Impact of AI and Big Data on Business and Society","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Value (mathematics); Shapley value; Knowledge management; Business; Industrial organization; Computer science; Economics; Microeconomics; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01498966,0.0005162123,0.0006740273,0.004988879,0.0005168417,0.002160764,0.0006723435,0.0008360812,0.002194161],"category_scores_gemma":[0.0663623,0.0002601036,0.0009426645,0.005390537,0.001426826,0.002611142,0.001498843,0.001035616,0.0002171147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001330647,"about_ca_system_score_gemma":0.000831909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001106937,"about_ca_topic_score_gemma":0.0009433159,"domain_scores_codex":[0.9934422,0.003288228,0.0004828096,0.0004308331,0.001966647,0.0003893184],"domain_scores_gemma":[0.8433981,0.1351439,0.01042283,0.004722753,0.004682243,0.001630076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004291735,0.0005133427,0.8696885,0.0002721743,0.001286587,0.000193675,0.001530178,0.03798633,0.001077355,0.01781023,0.0006118887,0.06860065],"study_design_scores_gemma":[0.00004892707,0.002257907,0.8198121,0.0001436728,0.0003391502,0.0001905876,0.003196064,0.1345351,0.001870217,0.03614468,0.001324969,0.000136599],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749225,0.0003917365,0.01478292,0.000240981,0.00002369884,0.00008850243,0.0001853263,0.00002823388,0.009335987],"genre_scores_gemma":[0.9973416,0.00009261538,0.002239165,0.00001227785,0.00001309259,0.00003337857,0.00009162834,0.000004092314,0.0001722933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01498966,"threshold_uncertainty_score":0.07927382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6344555174748078,"score_gpt":0.5082892247499552,"score_spread":0.1261662927248526,"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."}}