{"id":"W2595369245","doi":"10.3390/polym9030110","title":"Preparation of Microporous Polypropylene/Titanium Dioxide Composite Membranes with Enhanced Electrolyte Uptake Capability via Melt Extruding and Stretching","year":2017,"lang":"en","type":"article","venue":"Polymers","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"China Scholarship Council; National Natural Science Foundation of China; National Science Foundation","keywords":"Materials science; Crystallinity; Membrane; Polypropylene; Microporous material; Chemical engineering; Scanning electron microscope; Composite number; Electrolyte; Titanium dioxide; Differential scanning calorimetry; Lamellar structure; Composite material; Chemistry","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":[0.0001912393,0.0001912702,0.000250809,0.00004226905,0.0003824542,0.00006199449,0.0003326238,0.00008166975,0.000142744],"category_scores_gemma":[0.00004430763,0.0001641779,0.00003826201,0.00007504668,0.0006418257,0.0005213986,0.0001488386,0.0001151812,0.00001129492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007814812,"about_ca_system_score_gemma":0.00001340402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001354212,"about_ca_topic_score_gemma":0.0007101126,"domain_scores_codex":[0.9987211,0.00003217064,0.000278194,0.0004222192,0.0002665094,0.0002798695],"domain_scores_gemma":[0.9988934,0.00003617365,0.0003669133,0.000625948,0.00001157506,0.00006603106],"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":[0.0001317456,0.00002514259,0.006070669,0.00002661804,0.00002263699,0.000001918747,0.0005182712,0.00009889871,0.9829584,0.00003712241,0.000003921406,0.01010461],"study_design_scores_gemma":[0.0003278879,0.0001412162,0.0304598,0.00001746172,0.00002853553,0.00001328061,0.0001938997,0.0006197242,0.9678833,0.000106127,0.00002573039,0.0001829781],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944717,0.0001808692,0.001465822,0.0002052335,0.00004418986,0.0002832511,0.000005083924,0.00009271815,0.003251175],"genre_scores_gemma":[0.9973121,0.00005453129,0.00240055,0.00002455555,0.00001186492,0.00001547315,0.000003814412,0.00001621225,0.0001608657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02438913,"threshold_uncertainty_score":0.6694981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008341060118710636,"score_gpt":0.2553764325430072,"score_spread":0.2470353724242966,"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."}}