{"id":"W4221042328","doi":"10.1002/aelm.202101377","title":"Comprehensive Study on High Purity Semiconducting Carbon Nanotube Extraction","year":2022,"lang":"en","type":"article","venue":"Advanced Electronic Materials","topic":"Carbon Nanotubes in Composites","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kinova (Canada); National Research Council Canada","funders":"Defense Advanced Research Projects Agency; National Science Foundation","keywords":"Carbon nanotube; Materials science; Very-large-scale integration; Nanotechnology; Transistor; Voltage; Electrical engineering; Computer science; Embedded system","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":[0.0002884444,0.0003055361,0.0002448297,0.0004203389,0.0002749111,0.0002754729,0.0001402115,0.0002807043,0.0005956594],"category_scores_gemma":[0.0003288093,0.000117278,0.0001959303,0.0004910899,0.0001589487,0.0003195623,0.0001863848,0.0001765319,0.00028932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002147597,"about_ca_system_score_gemma":0.0002955235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008148941,"about_ca_topic_score_gemma":0.001757824,"domain_scores_codex":[0.9998162,0.00001665343,0.000008924912,0.00004426083,0.00009925303,0.00001467758],"domain_scores_gemma":[0.999821,0.00003233294,0.0000328648,0.00001674256,0.000085464,0.00001163685],"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":[0.000021182,0.0000145718,0.000561943,0.0001164346,0.000008965028,0.00006371752,0.00002356995,0.0002799323,0.9919121,0.0001954222,0.0001128569,0.006689304],"study_design_scores_gemma":[0.000003259696,0.0001198356,0.002654165,0.00001293628,0.00002579394,0.00009423599,0.00001866965,0.001709271,0.9913378,0.00005667778,0.003960722,0.000006648455],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752015,0.004849407,0.01253249,0.0001016685,0.00005061531,0.0001002211,0.0005593313,0.0001053001,0.006499426],"genre_scores_gemma":[0.9807035,0.003773641,0.0111752,0.00008889691,0.00002202057,0.00005274024,0.000772415,0.00004663801,0.003364964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008148941,"threshold_uncertainty_score":0.001992702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360169981224907,"score_gpt":0.2820497598375654,"score_spread":0.2684480600253163,"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."}}