{"id":"W2753803825","doi":"","title":"新規なクロロメチル化ポリスチレン‐2‐アデニンのキレート樹脂の合成とキャラクタリゼーションおよび食用きのこ試料中における水銀イオン濃度の事前濃縮と検出へのその利用","year":2016,"lang":"ja","type":"article","venue":"Canadian Journal of Chemistry","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Chemistry; Stereochemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003405147,0.0003237305,0.0002030398,0.0006006489,0.001469217,0.001270779,0.0004248257,0.0007200714,0.01942344],"category_scores_gemma":[0.0005728689,0.0003089251,0.0003135417,0.0003970144,0.001352978,0.001100865,0.0004757772,0.0008923031,0.005450702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009785248,"about_ca_system_score_gemma":0.001167287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006729711,"about_ca_topic_score_gemma":0.005854355,"domain_scores_codex":[0.9996541,0.0000269546,0.00001325726,0.00009308854,0.0001412124,0.00007149364],"domain_scores_gemma":[0.9996947,0.00005632433,0.00003228862,0.00003360028,0.0001414715,0.00004167394],"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":[0.0007886049,0.0003022359,0.009001459,0.0006762996,0.0001104723,0.001936917,0.003191314,0.004191848,0.3964446,0.3435665,0.02850384,0.2112859],"study_design_scores_gemma":[0.00008198416,0.0004639849,0.01737675,0.00009757694,0.0001051762,0.002154078,0.003025071,0.005026391,0.4845132,0.0797099,0.4072678,0.0001781222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2883969,0.006577459,0.0417905,0.003258514,0.00184079,0.0002127843,0.0006279832,0.00042405,0.6568709],"genre_scores_gemma":[0.804446,0.002576475,0.01609112,0.000878603,0.0002851638,0.00009470032,0.0004132358,0.00008811649,0.1751266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01942344,"threshold_uncertainty_score":0.06497794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005739757609572673,"score_gpt":0.1720470099482309,"score_spread":0.1663072523386582,"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."}}