{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003391131,0.0003382381,0.000312544,0.0004379702,0.0004119191,0.0005825643,0.0007181338,0.0005228709,0.003981678],"category_scores_gemma":[0.0006845757,0.0001173641,0.0001477966,0.0002528594,0.0002180283,0.0008354982,0.0006341291,0.0003650756,0.0008275707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004354715,"about_ca_system_score_gemma":0.0004235469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005773836,"about_ca_topic_score_gemma":0.0004715655,"domain_scores_codex":[0.9996133,0.00007866298,0.00002119023,0.00007494722,0.000166745,0.00004513962],"domain_scores_gemma":[0.9995903,0.00008916674,0.00004405062,0.00007155503,0.0001688628,0.00003595852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001260219,0.0002800905,0.007852294,0.0005963595,0.00006647303,0.001281679,0.0009297591,0.02210428,0.3762242,0.02303786,0.01434394,0.5520229],"study_design_scores_gemma":[0.000259262,0.001178586,0.006189801,0.0001185838,0.0001557795,0.002520462,0.0003514193,0.6068008,0.2581845,0.007725878,0.1164077,0.0001073113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1760592,0.001157624,0.7986109,0.0004269536,0.0003393233,0.0003370421,0.0003053398,0.01151047,0.01125311],"genre_scores_gemma":[0.8984954,0.0003091281,0.09142753,0.0001236682,0.00009968548,0.0001694786,0.0003466617,0.00008370313,0.008944813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003981678,"threshold_uncertainty_score":0.01332003,"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."}}