{"id":"W1970989126","doi":"10.1108/14691930210435589","title":"Intellectual capital ROI: a causal map of human capital antecedents and consequents","year":2002,"lang":"en","type":"article","venue":"Journal of Intellectual Capital","topic":"Intellectual Capital and Performance Analysis","field":"Business, Management and Accounting","cited_by":799,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Intellectual capital; Human capital; Organizational capital; Structural capital; Knowledge management; Sample (material); Human resource management; Business; Human resources; Financial capital; Individual capital; Economic capital; Accounting; Economics; Finance; Management; Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006368324,0.0006246931,0.001107026,0.001589062,0.0003695101,0.0003730074,0.0007362841,0.0002601407,0.01295632],"category_scores_gemma":[0.001504351,0.0005295518,0.0006200409,0.0007249161,0.0006837514,0.00187237,0.0003999731,0.0008693269,0.001232934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001391153,"about_ca_system_score_gemma":0.00005887339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004096984,"about_ca_topic_score_gemma":0.0001654032,"domain_scores_codex":[0.995977,0.00005579791,0.001707128,0.0004555314,0.001063633,0.0007408411],"domain_scores_gemma":[0.9967935,0.0004800939,0.001110679,0.0003246824,0.001166809,0.0001242068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.005057294,0.007222759,0.03804949,0.003461351,0.007836048,0.002298426,0.278338,0.0003127495,0.1234814,0.01714646,0.4952635,0.02153251],"study_design_scores_gemma":[0.05380398,0.04164454,0.02182333,0.007693911,0.01304995,0.01842052,0.4014294,0.06409696,0.1557622,0.06822627,0.1303858,0.02366312],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915904,0.002793728,0.0001536154,0.0002895033,0.0009021425,0.0002248754,0.00001717184,0.00004529678,0.003983294],"genre_scores_gemma":[0.9958397,0.0003167019,0.00006688941,0.000427433,0.001506465,0.000005217739,0.00002062699,0.00007447883,0.001742487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3648777,"threshold_uncertainty_score":0.9997156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651043084761113,"score_gpt":0.2353228498007377,"score_spread":0.2088124189531266,"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."}}