{"id":"W3038546681","doi":"10.3390/s20133760","title":"Intuitive Development to Examine Collaborative IoT Supply Chain System Underlying Privacy and Security Levels and Perspective Powering through Proactive Blockchain","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer security; Computer science; Supply chain; Scalability; Leverage (statistics); Adversarial system; Authentication (law); Business","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.0002662278,0.0002932824,0.000364641,0.0001196922,0.000418785,0.0001099268,0.0003851649,0.0001499895,0.000002830517],"category_scores_gemma":[0.0001552349,0.0002936813,0.00002319734,0.0009883831,0.0001676466,0.00009966714,0.0007061816,0.0003266856,0.000009461672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002754495,"about_ca_system_score_gemma":0.0001365111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006161262,"about_ca_topic_score_gemma":0.00002855042,"domain_scores_codex":[0.9980288,0.0001309685,0.0002885202,0.000954276,0.0002223055,0.000375173],"domain_scores_gemma":[0.9988939,0.0001539715,0.0001268465,0.0003218489,0.0002943148,0.0002091572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004398864,0.00008857873,0.0003443218,0.00009342715,0.0002086074,0.00006253249,0.498293,0.0001284497,0.002249239,0.4913183,0.00003929806,0.00713018],"study_design_scores_gemma":[0.004559969,0.00206524,0.02963636,0.0006183303,0.0001101185,0.0004928644,0.5224645,0.2256378,0.171482,0.03159807,0.007478995,0.003855685],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9295303,0.0003038761,0.06081348,0.006903506,0.00004250706,0.001277597,0.00003265956,0.0004039142,0.0006921588],"genre_scores_gemma":[0.9548471,0.000008362413,0.04463447,0.0003319035,0.00002736451,0.0001188098,0.000001256924,0.00001709684,0.00001365435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4597203,"threshold_uncertainty_score":0.9999515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163869935273263,"score_gpt":0.2701615082419682,"score_spread":0.2385228088892355,"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."}}