{"id":"W28894178","doi":"10.1038/s41598-017-11325-7","title":"レーリー散乱損失を低減した光ファイバの検討(光センサ, 一般)","year":2005,"lang":"en","type":"article","venue":"電子情報通信学会技術研究報告. OFT, 光ファイバ応用技術","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001966915,0.0002627699,0.0001402213,0.0003048608,0.0002289518,0.0002430414,0.0001462354,0.0001864937,0.003558605],"category_scores_gemma":[0.0001259383,0.00008594237,0.0001599339,0.0002646536,0.0003133624,0.0001360584,0.0002180501,0.0002191763,0.0007199664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000423336,"about_ca_system_score_gemma":0.0003237817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00135498,"about_ca_topic_score_gemma":0.003982577,"domain_scores_codex":[0.9999046,0.00001268189,0.000008185172,0.00002629572,0.00002987605,0.00001820361],"domain_scores_gemma":[0.9998988,0.00001194374,0.00003919885,0.000007738221,0.00002082393,0.00002147059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009053265,0.00008297421,0.006431724,0.0003879335,0.00003761119,0.0005168383,0.00006259161,0.0003356204,0.894882,0.001720589,0.0004448268,0.09419184],"study_design_scores_gemma":[0.00001750744,0.001492165,0.01978713,0.00002509748,0.00006261229,0.001271455,0.00008367496,0.0002324151,0.9134066,0.0003592763,0.0632427,0.00001930463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9427406,0.0301024,0.01014809,0.000606016,0.0004779283,0.000108825,0.0009517046,0.0001637674,0.01470076],"genre_scores_gemma":[0.9452211,0.01526425,0.008298837,0.0002609187,0.00008214053,0.0000544163,0.0009276617,0.00002085392,0.02986987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003558605,"threshold_uncertainty_score":0.01190472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005904030492845477,"score_gpt":0.3215472637324774,"score_spread":0.3156432332396319,"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."}}