{"id":"W4387573037","doi":"10.3390/info14100557","title":"Exploring Blockchain Research in Supply Chain Management: A Latent Dirichlet Allocation-Driven Systematic Review","year":2023,"lang":"en","type":"article","venue":"Information","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Blockchain; Latent Dirichlet allocation; Supply chain; Traceability; Decentralization; Supply chain management; Transparency (behavior); Computer science; Knowledge management; Data science; Process management; Business; Topic model; Marketing; Economics; Computer security","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00273529,0.0001090226,0.0002246318,0.001074677,0.0001756914,0.00009313143,0.0009523036,0.00006269068,0.00000288902],"category_scores_gemma":[0.00008804,0.0001035302,0.00003959129,0.003938232,0.00003509356,0.0008222231,0.0004067903,0.0002468258,0.0009426159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223827,"about_ca_system_score_gemma":0.00002298695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002864764,"about_ca_topic_score_gemma":0.0000103131,"domain_scores_codex":[0.9981989,0.0001405945,0.0006326029,0.0001957487,0.000476439,0.0003556915],"domain_scores_gemma":[0.9987375,0.0001155135,0.0001297185,0.0008236401,0.0001474197,0.00004627435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002500804,0.00007398608,0.0002249208,0.09876934,0.00004266683,0.00001903615,0.005250355,0.001214462,0.00001213704,0.8723564,0.002394828,0.01963936],"study_design_scores_gemma":[0.0008428885,0.00008361993,0.004985364,0.05375686,0.00003687216,0.00003086091,0.001562186,0.9113468,0.0002160083,0.02243563,0.004057508,0.0006454231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3067251,0.01166235,0.4086967,0.1895402,0.001756348,0.04671128,0.00006114594,0.01209246,0.02275447],"genre_scores_gemma":[0.9855402,0.006024227,0.002457141,0.0005324408,0.00001379807,0.005292664,0.00004932114,0.000007907629,0.00008230114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9101323,"threshold_uncertainty_score":0.9998353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08593418660446979,"score_gpt":0.3035484930459348,"score_spread":0.2176143064414651,"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."}}