{"id":"W47784895","doi":"","title":"Development of a Dry Bone MDCT Scanning Protocol for Archaeological Crania","year":2011,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Paleopathology and ancient diseases","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Scanner; Protocol (science); Computer science; Detector; Artificial intelligence; Tomography; Computer vision; Biomedical engineering; Medicine; Radiology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003064207,0.0002329828,0.0003116049,0.0002971326,0.0004591214,0.0000434668,0.0004362366,0.0001054811,0.0002484639],"category_scores_gemma":[0.00003326865,0.0002207667,0.0001527896,0.00007293672,0.0005238922,0.0006229911,0.0002080428,0.0001994117,0.00005597738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263528,"about_ca_system_score_gemma":0.0001341814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001530194,"about_ca_topic_score_gemma":0.001035904,"domain_scores_codex":[0.9986073,0.0001036663,0.0003148173,0.0003819521,0.0001875968,0.0004046026],"domain_scores_gemma":[0.9991511,0.00005397373,0.0002257986,0.0002364151,0.0001754004,0.0001573499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006745072,0.0003668527,0.9743658,0.0002026776,0.00004995357,0.000136015,0.01859229,3.931528e-7,0.0003239795,0.004585251,8.656334e-7,0.0007013643],"study_design_scores_gemma":[0.002264909,0.0003202643,0.9584528,0.0003414617,0.00006940494,0.000006109205,0.002293048,1.989116e-7,0.002886717,0.0007724058,0.03214975,0.0004428882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848723,0.000009951816,0.0005437191,0.00001396564,0.0001024695,0.01217232,0.0000378746,0.0001128326,0.002134509],"genre_scores_gemma":[0.9913544,6.600061e-7,0.001043083,0.0001365881,0.0001055617,0.002104425,0.00001561676,0.00002504492,0.005214619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03214888,"threshold_uncertainty_score":0.9002603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2776270196497846,"score_gpt":0.3385669586771275,"score_spread":0.0609399390273429,"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."}}