{"id":"W2337694841","doi":"","title":"실내의 라돈 방출과 환기에 의한 저감방안","year":2014,"lang":"ko","type":"article","venue":"한국태양에너지학회 추계학술발표회 논문집","topic":"Energy and Environmental Systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radon; Gypsum; Environmental science; Apartment; Waste management; Ventilation (architecture); Environmental engineering; Engineering; Civil engineering; Materials science; Metallurgy; Mechanical engineering; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002535337,0.0003200983,0.0002330041,0.0006260069,0.0005099351,0.0009266616,0.0002862301,0.0003634388,0.007176216],"category_scores_gemma":[0.0003532985,0.0001899486,0.0003460681,0.0006929058,0.0002737363,0.0005077752,0.0003333503,0.0004113231,0.002941049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004709606,"about_ca_system_score_gemma":0.0005767467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004461398,"about_ca_topic_score_gemma":0.005209131,"domain_scores_codex":[0.999554,0.00004259604,0.00002464889,0.0001211046,0.0001972014,0.00006043481],"domain_scores_gemma":[0.9997472,0.0000229503,0.00005686383,0.00001871552,0.0001329027,0.00002138958],"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":[0.0005615968,0.0003072578,0.1452804,0.001124114,0.0002321765,0.001549457,0.001156945,0.001686541,0.3542757,0.007269502,0.01286614,0.4736902],"study_design_scores_gemma":[0.00003708742,0.0009616388,0.3487287,0.0002020968,0.0003047484,0.003153566,0.002315345,0.005032955,0.2842411,0.004260439,0.3506284,0.000133871],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8373808,0.01331196,0.02582651,0.001300858,0.0004816555,0.0002576475,0.002579839,0.000675159,0.1181855],"genre_scores_gemma":[0.9241355,0.005428661,0.01103099,0.0005732128,0.00007825776,0.00008420135,0.002659452,0.00005882352,0.05595088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007176216,"threshold_uncertainty_score":0.02400684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00938950241020484,"score_gpt":0.2305117666796725,"score_spread":0.2211222642694677,"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."}}