{"id":"W3020476608","doi":"10.1109/pcic30934.2019.9074504","title":"Applying Wireless Communications Technology to Industrial Trace Heating","year":2019,"lang":"en","type":"article","venue":"","topic":"Wireless Sensor Networks for Data Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shell (Canada); University of Alberta","funders":"","keywords":"Wireless; TRACE (psycholinguistics); Computer science; Telecommunications","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":[0.0004718555,0.0003350421,0.0001310662,0.0005051828,0.0003800745,0.0009180177,0.0004296711,0.0005217044,0.002156353],"category_scores_gemma":[0.001099391,0.000184957,0.0001588749,0.0009981475,0.0007127245,0.001252631,0.0006047235,0.0005886786,0.0005925614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005149117,"about_ca_system_score_gemma":0.0005530127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009123733,"about_ca_topic_score_gemma":0.001007456,"domain_scores_codex":[0.9996073,0.0001304157,0.000019016,0.00004338583,0.0001625318,0.00003731029],"domain_scores_gemma":[0.9996439,0.0001671969,0.00003754589,0.00005169487,0.00008712431,0.00001250111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000133725,0.0001365585,0.003691133,0.0007083078,0.00003851773,0.001276002,0.0006377291,0.033365,0.1414188,0.1220767,0.006974031,0.6895435],"study_design_scores_gemma":[0.00004261369,0.001280137,0.003880084,0.0004184009,0.0001016984,0.002760301,0.001121601,0.1119703,0.3311525,0.07406915,0.4730868,0.0001164491],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05255584,0.007461236,0.8835508,0.002176375,0.000458089,0.0001388347,0.00004505403,0.0006672218,0.05294652],"genre_scores_gemma":[0.6628879,0.01810339,0.2816006,0.000647197,0.0004298326,0.0001532,0.00006779536,0.0001116417,0.03599854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002156353,"threshold_uncertainty_score":0.007213712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03211080409841463,"score_gpt":0.2821645041780429,"score_spread":0.2500537000796282,"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."}}