{"id":"W2892570462","doi":"10.2524/jtappij.72.705","title":"Activities for Energy Saving in PM8","year":2018,"lang":"en","type":"article","venue":"JAPAN TAPPI JOURNAL","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Miller Group (Canada)","funders":"","keywords":"Energy (signal processing); Chemistry; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004921636,0.00007668693,0.00009598024,0.00004102103,0.0002611643,0.00005491101,0.0001355655,0.0000436496,0.0003113352],"category_scores_gemma":[0.0000780827,0.00006869361,0.0000486847,0.00009386899,0.0001189123,0.0002208098,0.00005770428,0.0001297477,0.00002254048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001593451,"about_ca_system_score_gemma":0.000009592837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001178569,"about_ca_topic_score_gemma":0.0001040523,"domain_scores_codex":[0.9992145,0.00003932804,0.0001823727,0.0001207622,0.0001631519,0.0002799347],"domain_scores_gemma":[0.9996601,0.00007997006,0.0001005794,0.00007648439,0.000006034643,0.00007681553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001342832,0.0001569222,0.2654534,0.00001282977,0.00002786117,0.00001119051,0.01027069,0.0008208769,0.04282288,0.0004844299,0.01258429,0.6672203],"study_design_scores_gemma":[0.003836763,0.001941403,0.4498973,0.0005429169,0.00005140924,0.0007866055,0.01603645,0.02762214,0.05188832,0.0232036,0.4225163,0.001676763],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860431,0.00001613372,0.006586934,0.0001714701,0.0004815452,0.00003052339,0.000001214511,0.00001632205,0.006652758],"genre_scores_gemma":[0.9938155,0.000006008655,0.00349171,0.00009007607,0.001097948,0.000004861949,3.683439e-7,0.00001051389,0.001482951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6655436,"threshold_uncertainty_score":0.3408902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02345214918704758,"score_gpt":0.2664453954427894,"score_spread":0.2429932462557419,"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."}}