{"id":"W4392804777","doi":"10.37904/nanocon.2023.4790","title":"Research technology of the core nanoyarn for Filtration Application","year":2023,"lang":"en","type":"article","venue":"NANOCOM ...","topic":"Engineering Technology and Methodologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Core (optical fiber); Filtration (mathematics); Computer science; Telecommunications; Mathematics","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":[0.0003506129,0.0003328285,0.0002736364,0.0004745789,0.0003207579,0.0005678648,0.0003441113,0.0005293086,0.001750674],"category_scores_gemma":[0.0001533668,0.0001491736,0.00027883,0.0003562912,0.0002108161,0.0006437267,0.0003240603,0.0004275893,0.001214527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006822541,"about_ca_system_score_gemma":0.0007155702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000692419,"about_ca_topic_score_gemma":0.0004824421,"domain_scores_codex":[0.9997931,0.00001517175,0.000007753682,0.00005056991,0.0001074827,0.00002588722],"domain_scores_gemma":[0.9998437,0.0000168831,0.0000226271,0.00001643491,0.00008317817,0.00001711252],"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":[0.00005759702,0.00005803017,0.0005155738,0.0007493958,0.00001259049,0.000178034,0.0001452647,0.001188091,0.8764627,0.01758648,0.002079112,0.1009671],"study_design_scores_gemma":[0.000009644743,0.000351508,0.001989039,0.00009697578,0.00002432795,0.0008603554,0.00007423353,0.007240342,0.8579953,0.002827614,0.1285038,0.00002687358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3168989,0.111745,0.4145359,0.002824628,0.001795227,0.0003138822,0.0005276331,0.001132083,0.1502269],"genre_scores_gemma":[0.7246752,0.05138347,0.1474787,0.0006097946,0.0004351817,0.0002257465,0.0005655675,0.0001825875,0.07444373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001750674,"threshold_uncertainty_score":0.005856574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1100228528369276,"score_gpt":0.374307661603343,"score_spread":0.2642848087664154,"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."}}