{"id":"W2081201826","doi":"10.5267/j.msl.2013.12.020","title":"A new approach for measuring human resource accounting","year":2014,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Competency Development and Evaluation","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human resource accounting; Human resources; Analytic hierarchy process; Knowledge management; Valuation (finance); Human resource management; Human capital; Accounting; Process (computing); Business; Management accounting; Process management; Management science; Computer science; Management; Operations research; Economics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002561399,0.0001001087,0.00008654817,0.0002957852,0.0004632859,0.0001503864,0.0005575162,0.00001671561,0.0001513908],"category_scores_gemma":[0.0000252218,0.0001001878,0.0000379741,0.0004465416,0.00007667269,0.000186234,0.0001209764,0.00005433913,0.0001059267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007013142,"about_ca_system_score_gemma":0.000004366558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001835089,"about_ca_topic_score_gemma":0.000001331727,"domain_scores_codex":[0.998435,0.00003177667,0.0001741737,0.0004923108,0.0004516858,0.0004151167],"domain_scores_gemma":[0.9995021,0.00002590544,0.00007667817,0.0003294064,0.00001211426,0.0000538586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005368632,0.0001368726,0.04972719,0.0001880547,0.0001327658,0.000003681798,0.008393892,0.002720552,0.03201907,0.1617926,0.387255,0.3575765],"study_design_scores_gemma":[0.00308173,0.00007013663,0.6336103,0.00006872983,0.0001125699,0.000003771132,0.002355289,0.01037608,0.0006386584,0.002493621,0.3462291,0.0009599872],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1004412,0.000004269596,0.60446,0.003148903,0.0004103093,0.0005848334,1.20824e-7,0.00009779108,0.2908526],"genre_scores_gemma":[0.9340649,1.224521e-7,0.05368822,0.004844894,0.0002957042,0.0001128198,0.000008336477,0.00001633436,0.006968684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8336237,"threshold_uncertainty_score":0.4085539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0583382576303307,"score_gpt":0.3079595261505568,"score_spread":0.2496212685202261,"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."}}