{"id":"W2799611922","doi":"10.1016/j.crme.2018.04.008","title":"Diffuse manifold learning of the geometry of woven reinforcements in composites","year":2018,"lang":"en","type":"article","venue":"Comptes Rendus Mécanique","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; FDC Composites (Canada)","funders":"","keywords":"Kernel (algebra); Manifold (fluid mechanics); Woven fabric; Geometry; Feature (linguistics); Space (punctuation); Computer science; Composite material; Artificial intelligence; Mathematics; Materials science; Engineering; Mechanical engineering; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004723636,0.0005732971,0.0005054604,0.0008977096,0.0002321928,0.0006611484,0.0007150641,0.0006777905,0.0006076266],"category_scores_gemma":[0.001903455,0.0004165227,0.0006516761,0.0004519659,0.00102222,0.001019599,0.0007984263,0.001029165,0.0002762337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004558058,"about_ca_system_score_gemma":0.0004074841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002053114,"about_ca_topic_score_gemma":0.002461245,"domain_scores_codex":[0.999795,0.00005742582,0.000007804018,0.00006784358,0.00004999377,0.00002208046],"domain_scores_gemma":[0.9993982,0.0002273586,0.00009628722,0.0001378646,0.0001013201,0.00003901636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007719034,0.00003602061,0.001813122,0.00006499657,0.00003156236,0.00008422331,0.0001556507,0.894962,0.01596569,0.01324755,0.00083382,0.07272814],"study_design_scores_gemma":[0.000001349379,0.00001045169,0.0003344814,0.000002132948,0.000001426642,0.00001593505,0.00001137592,0.9925234,0.0009824302,0.00592748,0.0001839739,0.000005559376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09220646,0.000131049,0.906608,0.0001027223,0.00001191274,0.00001606028,0.00006618629,0.0004298017,0.0004279066],"genre_scores_gemma":[0.83495,0.0003018826,0.1629027,0.00004318011,0.00003555427,0.00004297896,0.0003285646,0.0001242275,0.001270905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002053114,"threshold_uncertainty_score":0.004082382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391736411789474,"score_gpt":0.2551770309587909,"score_spread":0.2312596668408962,"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."}}