{"id":"W1582307787","doi":"","title":"The influence of cutting parameters on the surface quality of routed paper birch and surface roughness prediction modeling.","year":2009,"lang":"en","type":"article","venue":"Wood and Fiber Science (Society of Wood Science and Technology)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Surface roughness; Artificial neural network; Machining; Surface finish; Response surface methodology; Regression analysis; Orientation (vector space); Linear regression; Materials science; Grain size; Surface (topology); Process (computing); Mechanical engineering; Composite material; Engineering; Computer science; Mathematics; Machine learning; Geometry","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":[0.001744551,0.0001131942,0.0001667269,0.00006019183,0.0005292773,0.00006549122,0.0004109084,0.00008749554,4.477958e-7],"category_scores_gemma":[0.0001647832,0.00007132012,0.00002210869,0.00142397,0.002394805,0.0004865747,0.00009405851,0.0001670995,9.196174e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001773969,"about_ca_system_score_gemma":0.00006433285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002775011,"about_ca_topic_score_gemma":0.000001761493,"domain_scores_codex":[0.9987207,0.00001035065,0.0002847258,0.0002872369,0.0004396205,0.0002573404],"domain_scores_gemma":[0.999226,0.00008655895,0.0001207092,0.0002688855,0.0002558488,0.00004201075],"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":[0.00001675074,0.00004920447,0.002772526,0.0001553648,0.00002013195,9.034127e-8,0.003198999,0.687419,0.2776052,0.003840053,0.00001947307,0.02490316],"study_design_scores_gemma":[0.0003034649,0.0002737909,0.01341124,0.000167333,0.00001518483,0.000002730924,0.00251969,0.7872788,0.1929775,0.002807472,0.00003680014,0.000206054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998008,0.000309941,0.0004352528,0.0009351653,0.0000255076,0.0001417543,0.00000443713,0.00005569963,0.00008431792],"genre_scores_gemma":[0.996226,0.0007873302,0.002939084,0.00003448968,0.000002152298,0.000001510383,1.587524e-7,0.00000329887,0.000006002015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09985976,"threshold_uncertainty_score":0.8823761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128297972813882,"score_gpt":0.2307812435519991,"score_spread":0.2179514462706109,"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."}}