{"id":"W578432770","doi":"10.18999/sumrua.12.169","title":"British Columbiaから採取された獣骨および人骨のAMS ^C年代","year":2001,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography","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":[0.0002365536,0.0003878011,0.0001729643,0.001038043,0.003346351,0.001225602,0.0003114363,0.000282376,0.0146831],"category_scores_gemma":[0.0003697623,0.0002365164,0.0001135032,0.001626657,0.0003858566,0.0002272875,0.0003784965,0.0005934858,0.003302954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007490497,"about_ca_system_score_gemma":0.008153321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9351522,"about_ca_topic_score_gemma":0.9855657,"domain_scores_codex":[0.9995589,0.0000121425,0.00001389929,0.0001275653,0.0001946439,0.00009277659],"domain_scores_gemma":[0.9993435,0.0000176292,0.00003606089,0.00002402434,0.0005078657,0.00007088412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006971006,0.0003023639,0.4746016,0.0003977483,0.000116063,0.001114969,0.003004349,0.0007553235,0.1522069,0.003188735,0.07304423,0.2905706],"study_design_scores_gemma":[0.00002663093,0.0000501709,0.7952972,0.00008419708,0.00004549523,0.0002079078,0.001614437,0.0004714018,0.02105692,0.0002110301,0.1808799,0.00005475774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8463053,0.001909251,0.00208114,0.0007456792,0.0001810696,0.0002378386,0.0226985,0.0002213965,0.1256198],"genre_scores_gemma":[0.7919768,0.002367953,0.0093414,0.0009341168,0.00003722054,0.0002168246,0.01557573,0.0001500228,0.1794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06484777,"threshold_uncertainty_score":0.1304593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204048474954661,"score_gpt":0.2221103773623614,"score_spread":0.2100698926128148,"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."}}