{"id":"W4385637298","doi":"10.1177/00405175231189892","title":"Optimization of the quilting method and filling quality of cold-proof down clothing based on thermal insulation performance","year":2023,"lang":"en","type":"article","venue":"Textile Research Journal","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"China Scholarship Council","keywords":"Quilting; Thermal conductivity; Materials science; Bar (unit); Thermal insulation; Thermal resistance; Composite material; Clothing; Work (physics); Thermal; Engineering drawing; Mechanical engineering; Engineering; Thermodynamics; Physics","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":[0.01581623,0.0000777834,0.0001860068,0.0002136869,0.0005807501,0.0001163177,0.0002596455,0.00005703819,0.0004643046],"category_scores_gemma":[0.001454657,0.00005311961,0.00004721763,0.0005376096,0.000140749,0.0002344938,0.0001283656,0.0002442301,0.000007957179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005487762,"about_ca_system_score_gemma":0.0001974761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005373679,"about_ca_topic_score_gemma":0.000001733187,"domain_scores_codex":[0.9965066,0.001474961,0.0005384317,0.0001539956,0.001045648,0.0002804098],"domain_scores_gemma":[0.9980214,0.0008540073,0.0003528029,0.0002302729,0.0004838389,0.00005762843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004661518,0.00001799427,0.0006139552,0.00006452504,0.000002199763,1.879561e-7,0.0004146307,0.4779125,0.5188631,0.0001234793,0.00001367604,0.001927172],"study_design_scores_gemma":[0.0003855152,0.0001023635,0.06059732,0.0002286031,0.000005314561,0.000002341901,0.0002018415,0.6671697,0.2710668,0.0001615733,0.00001891147,0.00005967757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907941,0.00002113527,0.008125544,0.0002749088,0.0001619939,0.000233304,0.00001980864,0.0000174732,0.000351715],"genre_scores_gemma":[0.9949407,0.00002394531,0.004857371,0.00001302978,0.0000918013,0.00001027576,0.000002455499,0.00001211037,0.00004833722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2477963,"threshold_uncertainty_score":0.5481621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1736512187177911,"score_gpt":0.44312207516271,"score_spread":0.2694708564449189,"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."}}