{"id":"W4328123573","doi":"10.1111/poms.13980","title":"Securing containerized supply chain through public and private partnership","year":2023,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Toronto Metropolitan University","funders":"","keywords":"Incentive; General partnership; Business; Government (linguistics); Externality; Adversary; Public–private partnership; Public good; Supply chain; Industrial organization; Finance; Economics; Marketing; Computer security; Microeconomics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002358314,0.0000938751,0.00009593592,0.0001363356,0.0002468219,0.0001416693,0.00004248904,0.00002383258,0.00003659859],"category_scores_gemma":[0.00003320846,0.00008718228,0.00001846489,0.0004256683,0.00004530179,0.0003337295,0.00004166313,0.00006867461,0.00001374354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002261371,"about_ca_system_score_gemma":0.000002670218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005889663,"about_ca_topic_score_gemma":0.0000495817,"domain_scores_codex":[0.9993601,0.00002714843,0.0001406608,0.0002157421,0.00009234028,0.0001640024],"domain_scores_gemma":[0.9997692,0.000006395589,0.000007965047,0.0001568611,0.00002267273,0.00003693705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002261987,0.00006437679,0.007291896,0.00103535,0.0005893998,0.00001496835,0.007339144,0.6605138,0.006673202,0.2567414,0.007328906,0.05238495],"study_design_scores_gemma":[0.001670787,0.0001054055,0.05706078,0.0001335263,0.0002987099,0.00003480708,0.01124942,0.7109724,0.01069549,0.008545825,0.1978583,0.001374619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789948,0.0002710012,0.009467814,0.006661846,0.0002740752,0.0005498948,0.000002528815,0.0005815366,0.003196534],"genre_scores_gemma":[0.9966014,0.001216024,0.001053316,0.00006389501,0.00009203967,0.00008625587,0.00002586518,0.000009531054,0.0008516407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2481956,"threshold_uncertainty_score":0.3555191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784285542733001,"score_gpt":0.2449536626351953,"score_spread":0.2271108072078653,"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."}}