{"id":"W2898566836","doi":"10.1109/services.2018.00015","title":"Pattern Recognition on Usage of Operational Clothing in Canadian Armed Forces","year":2018,"lang":"en","type":"article","venue":"","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clothing; Point (geometry); Operational costs; Business; Database transaction; Transaction data; Computer science; Operations management; Operations research; Marketing; Engineering; Database","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":[0.0004038088,0.0004430518,0.0002717382,0.004838411,0.0009507205,0.001133639,0.0007469442,0.0004018029,0.002520159],"category_scores_gemma":[0.002457649,0.0001261695,0.0003840064,0.005923806,0.0004953572,0.0005409538,0.0005046867,0.0003374016,0.000801794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003178464,"about_ca_system_score_gemma":0.002168802,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7666832,"about_ca_topic_score_gemma":0.8412825,"domain_scores_codex":[0.9992456,0.00004120622,0.00004082871,0.0001183683,0.000359967,0.0001939933],"domain_scores_gemma":[0.9980733,0.0001963635,0.0002974727,0.0000907334,0.001201523,0.0001404628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000569723,0.0001461971,0.6957172,0.0003766337,0.0001234325,0.00094981,0.003659555,0.003400862,0.01623282,0.0009939936,0.01241367,0.2654161],"study_design_scores_gemma":[0.000002932393,0.00006075315,0.971255,0.00005275572,0.00003744274,0.0003146515,0.004396956,0.01194982,0.002675392,0.0001110607,0.009104949,0.00003826314],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854269,0.0004165679,0.002195742,0.00016329,0.00003475866,0.00005051369,0.004540766,0.0000988152,0.007072621],"genre_scores_gemma":[0.9892746,0.0003248151,0.002574659,0.00002762052,0.000007814152,0.00002490716,0.003309923,0.00001943132,0.004436359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2333168,"threshold_uncertainty_score":0.4693816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04850870171404244,"score_gpt":0.2977130330878971,"score_spread":0.2492043313738547,"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."}}