{"id":"W4405938100","doi":"10.1109/acp/ipoc63121.2024.10809672","title":"Fiber Channel Skew Study for Multi-Fiber SDM","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Surface Polishing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Skew; Fiber; Computer science; Channel (broadcasting); Materials science; Telecommunications; Composite material","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":[0.0001249875,0.000156576,0.0001389653,0.00007373379,0.00003217452,0.00007506524,0.0001333858,0.00006119535,0.0002563097],"category_scores_gemma":[0.00002503063,0.0001405014,0.00006107038,0.0001182318,0.00001024554,0.0002232003,0.00004220877,0.0001351411,0.0002544835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006364971,"about_ca_system_score_gemma":0.000006424036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002306677,"about_ca_topic_score_gemma":0.00002922571,"domain_scores_codex":[0.9993018,0.000007305819,0.0001490583,0.0002012749,0.00008589787,0.0002546648],"domain_scores_gemma":[0.999626,0.0000728578,0.000005511633,0.0002215446,0.00002377255,0.00005032649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003565443,0.0007091368,0.000175978,0.001839041,0.001042937,0.0001194652,0.01096786,0.07626443,0.004332906,0.005943892,0.753178,0.1453907],"study_design_scores_gemma":[0.0006541416,0.0001922042,0.0002121917,0.0001337708,0.00006974179,0.000007322539,0.0003086696,0.4484822,0.02267274,0.004405275,0.5219916,0.0008701556],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02427329,0.001322716,0.9356848,0.0002909501,0.0009611059,0.002299215,0.00008835069,0.01700893,0.01807062],"genre_scores_gemma":[0.5631676,0.00002818465,0.3814476,0.00009561595,0.0002377431,0.000645505,0.0000150437,0.0002589512,0.05410375],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5542372,"threshold_uncertainty_score":0.5729479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04448004311612491,"score_gpt":0.3238601680668521,"score_spread":0.2793801249507272,"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."}}