{"id":"W3123380859","doi":"10.1108/jic-06-2020-0206","title":"Intellectual capital and supply chain resilience","year":2021,"lang":"en","type":"article","venue":"Journal of Intellectual Capital","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":202,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Supply chain; Structural equation modeling; Intellectual capital; Resilience (materials science); Relational capital; Business; Structural capital; Human capital; Supply chain management; Industrial organization; Supply chain risk management; Economics; Service management; Financial capital; Marketing; Computer science; Individual capital; Economic growth","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":[],"category_scores_codex":[0.0006446252,0.0003087079,0.0004526427,0.0006129489,0.0002376344,0.0005087142,0.0004540161,0.0001087435,0.002709189],"category_scores_gemma":[0.003589598,0.0002528163,0.0002320059,0.00074904,0.0002720742,0.001228135,0.0004417496,0.0004930819,0.0003357505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000755504,"about_ca_system_score_gemma":0.0001418845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009548241,"about_ca_topic_score_gemma":0.0001100931,"domain_scores_codex":[0.9976804,0.00003946613,0.0007389971,0.0003685021,0.000686095,0.0004866033],"domain_scores_gemma":[0.9980937,0.0005733915,0.0003704633,0.0002479434,0.0006470102,0.00006750439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002221601,0.002351224,0.03786281,0.001067752,0.001242352,0.007528776,0.0729918,0.001588228,0.02258817,0.04154117,0.6781662,0.1308499],"study_design_scores_gemma":[0.00931604,0.002353901,0.03305274,0.001563112,0.001092152,0.006264747,0.3750698,0.0148772,0.02808474,0.03015063,0.4936056,0.004569284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882667,0.003289945,0.001438926,0.001572346,0.001032212,0.0001397015,0.000002379047,0.00003436813,0.004223401],"genre_scores_gemma":[0.9943023,0.0008669648,0.0003458709,0.001390816,0.001586729,0.000003661396,0.000006849081,0.00003389022,0.001462939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.302078,"threshold_uncertainty_score":0.9999924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011146162566862,"score_gpt":0.2166329815540655,"score_spread":0.2065215199283969,"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."}}