{"id":"W3177594079","doi":"10.1515/ipp-2020-4072","title":"In Situ Visualization for Control of Nano-Fibrillation Based on Spunbond Processing Using a Polypropylene/Polyethylene Terephthalate System","year":2021,"lang":"en","type":"article","venue":"International Polymer Processing","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Materials science; Polypropylene; Microfiber; Polyethylene terephthalate; Composite material; Polymer; Fiber; Polyethylene; Scanning electron microscope; Nanoscopic scale; Composite number; Spinning; Volumetric flow rate; Nanotechnology","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":[0.0001467402,0.0001997536,0.0002853774,0.0002531823,0.0000697709,0.00009396514,0.00009391463,0.00009809629,0.000009365185],"category_scores_gemma":[0.00007303465,0.0002157767,0.00006251579,0.0002471585,0.00002711847,0.0004321421,0.00001247645,0.0000548957,8.994182e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001869732,"about_ca_system_score_gemma":0.000102635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001712348,"about_ca_topic_score_gemma":0.000005413654,"domain_scores_codex":[0.998641,0.00003709216,0.0005498809,0.0002710931,0.0002696321,0.0002313504],"domain_scores_gemma":[0.9993618,0.0000688931,0.0002046985,0.0001096301,0.0002119504,0.00004300182],"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":[0.00006250252,0.00001646962,0.0002484445,0.0004472763,0.00001220223,0.00000607514,0.00007468164,0.3824588,0.6129917,0.0002231608,8.59791e-7,0.003457835],"study_design_scores_gemma":[0.0006166314,0.0000114527,0.0001002505,0.0007334112,0.00001315522,0.00001621645,0.00004392612,0.4885798,0.5096812,0.00004424698,0.00003162664,0.0001281705],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4985141,0.0009438456,0.4978887,0.00006577458,0.0007450611,0.0001849904,0.00004264728,0.0001886085,0.001426281],"genre_scores_gemma":[0.9964422,0.000002976888,0.002990622,0.00006608068,0.0003018508,0.00001643761,0.00005207478,0.00006637504,0.00006139412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4979281,"threshold_uncertainty_score":0.8799117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01589017839479148,"score_gpt":0.2770358270478095,"score_spread":0.261145648653018,"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."}}