{"id":"W3196227224","doi":"10.1016/j.clay.2021.106240","title":"Outstanding in-situ CNTs on Fe-pillared nanoclay for high-performance polymer nanocomposites","year":2021,"lang":"en","type":"article","venue":"Applied Clay Science","topic":"Polymer Nanocomposites and Properties","field":"Materials Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Innotech Alberta; Alberta Innovates - Technology Futures","keywords":"Nanocomposite; Carbon nanotube; Materials science; Raman spectroscopy; Montmorillonite; X-ray photoelectron spectroscopy; Fourier transform infrared spectroscopy; Chemical engineering; Polymer; Composite material","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":[0.0001153432,0.0004549953,0.0002596244,0.0001358714,0.0001905968,0.0003231486,0.0002468033,0.0003771206,0.001111868],"category_scores_gemma":[0.0001681959,0.000188372,0.000189935,0.0001023525,0.0001674862,0.0003140078,0.0002693564,0.0005024612,0.0003901138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002999833,"about_ca_system_score_gemma":0.0001229002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005336895,"about_ca_topic_score_gemma":0.002209529,"domain_scores_codex":[0.9998745,0.000008482403,0.000007530619,0.00003844623,0.0000333446,0.00003768773],"domain_scores_gemma":[0.9998802,0.00002673862,0.00002948702,0.00001454278,0.00002611818,0.00002293471],"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":[0.00001709105,0.000006677935,0.00002370365,0.00002818974,0.000002532148,0.000031149,0.00001331837,0.00007015988,0.9990675,0.00003760452,0.00004205282,0.0006600029],"study_design_scores_gemma":[0.000001951021,0.00002354374,0.0002351151,0.000002016666,0.000003639784,0.00001551046,0.000007814563,0.0004873006,0.9988182,0.000007834935,0.0003946644,0.000002378169],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907084,0.0007149539,0.003660895,0.0001058774,0.00007536177,0.00001961641,0.0001541059,0.0002061547,0.004354652],"genre_scores_gemma":[0.9946648,0.0002946653,0.002637136,0.00002852149,0.0000139962,0.00001232507,0.00007505036,0.0000425613,0.002230847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001111868,"threshold_uncertainty_score":0.003719568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.015850131274446,"score_gpt":0.2397685029711795,"score_spread":0.2239183716967335,"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."}}