{"id":"W30225168","doi":"10.7717/peerj.5539","title":"粘着剥離の物理的メカニズムとその解析 Lesson1 粘着剤の剥離メカニズムとその解析","year":2006,"lang":"en","type":"article","venue":"コンバーテック","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","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":[0.0005254381,0.0003830246,0.0004605756,0.001046499,0.0006356494,0.0005935415,0.0004169797,0.0004849928,0.01851575],"category_scores_gemma":[0.00163779,0.0001719753,0.0002574442,0.0005249403,0.0006358108,0.0008664326,0.0003704638,0.0008072185,0.004131407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005164448,"about_ca_system_score_gemma":0.0005750577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003488299,"about_ca_topic_score_gemma":0.005882722,"domain_scores_codex":[0.9995907,0.00003561907,0.00002453024,0.0001408941,0.0001088748,0.00009928724],"domain_scores_gemma":[0.9985899,0.0002569003,0.0002620442,0.0001896773,0.0004217379,0.000279699],"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":[0.002167739,0.000488849,0.2620334,0.0005770162,0.0001981411,0.006357696,0.001043607,0.0005786074,0.5201065,0.004235779,0.003559907,0.1986527],"study_design_scores_gemma":[0.00006234691,0.001213044,0.7701813,0.0000590866,0.0002426546,0.01742578,0.001261776,0.003050968,0.1640221,0.005715008,0.03667364,0.00009246785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514487,0.003917056,0.009627337,0.000867273,0.0002349752,0.00008209181,0.0007605156,0.0005072604,0.03255476],"genre_scores_gemma":[0.9866129,0.0006117176,0.002146562,0.000108231,0.00004083027,0.00002839944,0.0003973229,0.00005155437,0.01000261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01851575,"threshold_uncertainty_score":0.06194133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706291534202402,"score_gpt":0.2904471040072147,"score_spread":0.2733841886651907,"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."}}