{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008498468,0.00007890757,0.0002031811,0.00001903391,0.00002078223,0.00001714659,0.00002592629,0.00005124924,0.0001329016],"category_scores_gemma":[0.00001736477,0.00006206992,0.00001574725,0.0000351967,0.0000189478,0.00005996317,0.00002289765,0.00002469952,0.000002977254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008424553,"about_ca_system_score_gemma":0.000005226118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000564397,"about_ca_topic_score_gemma":0.00001248475,"domain_scores_codex":[0.999535,0.00004488154,0.000194925,0.0000767921,0.00006617742,0.00008218769],"domain_scores_gemma":[0.9998515,0.0000071606,0.00003275328,0.00006448746,0.00002729619,0.00001682532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004238951,0.00002519456,0.0001381998,0.0002080109,0.000054238,0.000001182529,0.000481705,0.00001288522,0.998389,0.00004296462,0.00002650751,0.0005777242],"study_design_scores_gemma":[0.0002127116,0.0001109899,0.0001879289,0.00007795713,0.00003019532,0.000002756772,0.00007681565,0.00040897,0.9983506,0.00002200987,0.0004692024,0.00004983936],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966813,0.002702886,0.00001292069,0.0000406796,0.0001671127,0.000122836,0.0001134351,0.00006519408,0.00009368223],"genre_scores_gemma":[0.9993556,0.0002695602,0.00008550724,0.000003670996,0.00003994213,0.00003053501,0.00003498794,0.00001635412,0.0001638362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002674353,"threshold_uncertainty_score":0.2531138,"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."}}