{"id":"W4239863035","doi":"10.32920/ryerson.14653815","title":"Advanced diagnostic system for underground communication networks with ventilation on demand","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Interrupt; Transponder (aeronautics); Amplifier; Engineering; Electrical engineering; Control room; Communications system; Power (physics); Computer science; Telecommunications; Microcontroller","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"],"consensus_categories":[],"category_scores_codex":[0.0001037498,0.0002557057,0.0002563058,0.00006121185,0.00007091881,0.0001212554,0.0001759276,0.0001925037,0.000007125259],"category_scores_gemma":[0.00003275785,0.0002640822,0.00006483842,0.00007411908,0.00001306974,0.00008036883,0.00009472352,0.0004256094,0.000002926143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004250834,"about_ca_system_score_gemma":0.00001262533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006336792,"about_ca_topic_score_gemma":0.000017976,"domain_scores_codex":[0.9991782,0.00002776575,0.0002298893,0.0002445726,0.0001258948,0.0001936505],"domain_scores_gemma":[0.9987952,0.000488731,0.0000618839,0.000560347,0.00004796655,0.00004593436],"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":[0.00001461855,0.00001255762,0.00006901239,0.0006020083,0.0000928709,0.000002160678,0.00009706355,0.9976906,0.0002520192,0.0006247203,0.00004201256,0.0005003305],"study_design_scores_gemma":[0.0004049413,0.00005666994,0.0007784493,0.00270049,0.00005443936,0.00000557634,0.0004233113,0.9912615,0.003614504,0.00001086028,0.0003058084,0.0003834688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08266991,0.003553307,0.908406,0.00001106725,0.0007555555,0.0007744839,0.000003779758,0.0009535186,0.00287244],"genre_scores_gemma":[0.9680876,0.0001907708,0.0304989,0.000006515795,0.00007686309,0.0005139769,0.0004485987,0.0001095824,0.00006726375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8854176,"threshold_uncertainty_score":0.9999812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007016016995404565,"score_gpt":0.2177620486163979,"score_spread":0.2107460316209933,"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."}}