{"id":"W4389100640","doi":"10.1088/1757-899x/1293/1/012004","title":"Proposed holistic strategy for mechanical recycling of wind turbine blades for 3D printing and compression molding","year":2023,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Turbine; Process (computing); Process engineering; Scale (ratio); Molding (decorative); Blade (archaeology); Turbine blade; Mechanical engineering; Pellets; Compression molding; Environmental science; Manufacturing engineering; Computer science; Engineering; Materials science; Composite material","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":[0.0003099963,0.0005972377,0.0007030784,0.001048931,0.0007772741,0.001033932,0.001056593,0.001062726,0.00389332],"category_scores_gemma":[0.000154038,0.0003189648,0.0008118632,0.0003582863,0.0004211138,0.0005924756,0.0007504831,0.0003530993,0.001101996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005859589,"about_ca_system_score_gemma":0.0008627611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001244299,"about_ca_topic_score_gemma":0.001897895,"domain_scores_codex":[0.9997612,0.00002890107,0.00001350557,0.00004712755,0.0001066761,0.00004264267],"domain_scores_gemma":[0.9999359,0.000004887737,0.000009541775,0.00001287876,0.00002835254,0.000008403211],"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":[0.0002031155,0.0002732116,0.002207275,0.000761975,0.00008503051,0.00153368,0.0002067078,0.2804985,0.4591049,0.03901085,0.002318121,0.2137968],"study_design_scores_gemma":[0.00006594155,0.0008856629,0.002469309,0.0001252597,0.0001204702,0.001380604,0.0002619738,0.7930326,0.1675121,0.0101505,0.02389043,0.0001051963],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1182104,0.001153592,0.8370103,0.0005441316,0.0001718608,0.000414725,0.0001075556,0.001387129,0.04100043],"genre_scores_gemma":[0.7141438,0.0007093471,0.2687864,0.0001032715,0.00001889625,0.0002009625,0.0000920716,0.00006511362,0.01588016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00389332,"threshold_uncertainty_score":0.01302445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05358468959715892,"score_gpt":0.2709755475566055,"score_spread":0.2173908579594465,"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."}}