{"id":"W4225130189","doi":"10.1111/rssc.12572","title":"Stopping Time Detection of Wood Panel Compression: A Functional Time-Series Approach","year":2022,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series C (Applied Statistics)","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Simon Fraser University; British Columbia Institute of Technology","funders":"","keywords":"Univariate; Computer science; Sample (material); Series (stratigraphy); Algorithm; Statistics; Mathematics; Multivariate statistics","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002381835,0.0003668383,0.0009419995,0.00009429259,0.001466366,0.0001785392,0.001211235,0.0001129574,0.002080826],"category_scores_gemma":[0.002948992,0.00026219,0.0003101734,0.0007793746,0.001076595,0.0002976574,0.0008758194,0.001244887,0.00003833825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003622475,"about_ca_system_score_gemma":0.0002946565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007018252,"about_ca_topic_score_gemma":9.476821e-7,"domain_scores_codex":[0.9925048,0.0005124786,0.001954101,0.0005159035,0.003985558,0.0005271009],"domain_scores_gemma":[0.992687,0.003892616,0.001825158,0.0004900627,0.0008233137,0.0002818086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.008657907,0.002104842,0.0005105843,0.0004903298,0.001297938,0.0001097089,0.005325991,0.3950038,0.04637035,0.2530485,0.1615808,0.1254992],"study_design_scores_gemma":[0.004065361,0.002320651,0.01294181,0.00009241189,0.0006755631,0.0005721221,0.01310853,0.1868328,0.003911537,0.7332494,0.04065274,0.001577105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00193808,0.0001152349,0.9933044,0.0002043101,0.0008763734,0.0002911286,0.002020634,0.00003051096,0.001219295],"genre_scores_gemma":[0.5963044,0.00001009532,0.3980056,0.0001610687,0.0004801536,0.00005055085,0.00004318329,0.00007127551,0.004873737],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5952989,"threshold_uncertainty_score":0.999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04960986584693204,"score_gpt":0.2932683510259271,"score_spread":0.2436584851789951,"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."}}