{"id":"W2543088880","doi":"","title":"7.2.2 Metrical stress","year":2004,"lang":"en","type":"article","venue":"","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Stress (linguistics); Linguistics; Philosophy","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":[0.00003807328,0.00005719129,0.00005454493,0.00009596323,0.00001152536,0.0000146075,0.00009382793,0.00003674385,0.00009331065],"category_scores_gemma":[0.00001134464,0.00005145874,0.00001798633,0.0002691112,0.000008934749,0.00002685942,0.00001510208,0.0001333081,0.000344783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000063591,"about_ca_system_score_gemma":0.000005162498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009852706,"about_ca_topic_score_gemma":0.000002758087,"domain_scores_codex":[0.9995646,0.000001189946,0.00005842976,0.00006234425,0.0001301151,0.0001832453],"domain_scores_gemma":[0.999783,0.00001830322,0.000001188982,0.000118321,0.000008196723,0.00007099422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[5.106704e-7,0.00001331884,0.00005691329,0.00003042255,0.00001625725,0.00001124196,0.00002632647,0.975343,0.004848644,0.01625061,0.0006584865,0.002744261],"study_design_scores_gemma":[0.001924352,0.0000790223,0.006884929,0.00004890218,0.00001325637,0.00002950333,0.0001351868,0.1023628,0.8611927,0.003752665,0.02263017,0.0009465555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2876981,0.000483254,0.4108474,0.0001798922,0.0003433912,0.0001777336,0.000005870737,0.003258105,0.2970063],"genre_scores_gemma":[0.9926867,0.00001789584,0.007035001,0.000006509906,0.00004774993,0.000008873368,0.000001369953,0.0000205432,0.0001753695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8729802,"threshold_uncertainty_score":0.4431603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007644394965821514,"score_gpt":0.2171199218176505,"score_spread":0.209475526851829,"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."}}