{"id":"W2889848770","doi":"10.1002/pat.4453","title":"Piezoelectric property improvement of polyethylene ferroelectrets using postprocessing thermal‐pressure treatment","year":2018,"lang":"en","type":"article","venue":"Polymers for Advanced Technologies","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Materials science; Electret; Composite material; Polypropylene; Piezoelectricity; Polyethylene; Polymer; Piezoelectric coefficient; Thermal; Transverse plane; Extrusion; Structural engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001233909,0.0003364918,0.0001450181,0.00013361,0.00008527515,0.000182698,0.0001535423,0.0002655863,0.000556174],"category_scores_gemma":[0.0002990293,0.0001427359,0.0001579998,0.0001261253,0.0001333665,0.0002860203,0.0001633363,0.0002655744,0.0001439717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008320275,"about_ca_system_score_gemma":0.0000810929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001378889,"about_ca_topic_score_gemma":0.0004047119,"domain_scores_codex":[0.9999057,0.000009475743,0.000007697057,0.00002046427,0.00003625115,0.0000203436],"domain_scores_gemma":[0.9998493,0.00003640407,0.00005464872,0.00001400501,0.00003345404,0.00001216719],"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":[0.00001407279,0.000004534296,0.00007062822,0.00003211284,0.000001908026,0.00003986192,0.00001532134,0.00004990449,0.9984409,0.00001815059,0.0000081174,0.001304578],"study_design_scores_gemma":[0.000002690301,0.00008319893,0.001243783,0.000002346464,0.000005026843,0.00009802875,0.00001104258,0.0003335749,0.9975365,0.000007511707,0.0006729849,0.000003188286],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991098,0.0008380703,0.007316129,0.00003778387,0.00002748984,0.0000176364,0.00005190057,0.00003729615,0.000575643],"genre_scores_gemma":[0.9908771,0.0006652842,0.007113046,0.00003010234,0.00001155924,0.00002329294,0.0001087715,0.00001900373,0.001151847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000556174,"threshold_uncertainty_score":0.001860559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733838569718987,"score_gpt":0.2502620098106724,"score_spread":0.2329236241134826,"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."}}