{"id":"W3209036393","doi":"10.3390/ma14216314","title":"Prediction of Mechanical Properties of Artificially Weathered Wood by Color Change and Machine Learning","year":2021,"lang":"en","type":"article","venue":"Materials","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Color measurement; Weathering; Pulp and paper industry; Materials science; Mathematics; Composite material; Artificial intelligence; Computer science; Engineering; Geology","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":[0.0004800979,0.000531941,0.0003599603,0.0004936892,0.0001264871,0.0003370514,0.0003021222,0.0003912053,0.0003846828],"category_scores_gemma":[0.001199556,0.0001635311,0.0004082152,0.0003554837,0.0001872482,0.0003894267,0.0001076655,0.0003790913,0.0001115705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002932375,"about_ca_system_score_gemma":0.0002557693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003278614,"about_ca_topic_score_gemma":0.00553732,"domain_scores_codex":[0.9998654,0.00003301054,0.000008981468,0.00003872384,0.00003641771,0.0000174568],"domain_scores_gemma":[0.9993945,0.000374464,0.000070412,0.00004509721,0.00009828761,0.00001725181],"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":[0.0002049543,0.0003519752,0.03220888,0.00009081287,0.00007124735,0.00013531,0.00003538191,0.8187144,0.06753757,0.0002671708,0.0001595781,0.08022274],"study_design_scores_gemma":[0.000002619912,0.0000442776,0.01038369,0.000001998764,0.000007627096,0.00001755645,0.000005874123,0.9830446,0.006331717,0.00009432026,0.00005831738,0.000007266417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8788804,0.000176084,0.1200224,0.00002641002,0.00002024799,0.00002831896,0.0001489498,0.0002563493,0.0004408774],"genre_scores_gemma":[0.9822672,0.00005521754,0.01723084,0.000007999467,0.000004096051,0.00001748696,0.0001603973,0.00001056178,0.0002462305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003278614,"threshold_uncertainty_score":0.006519079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06243748790730529,"score_gpt":0.1894327202996863,"score_spread":0.126995232392381,"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."}}