{"id":"W2041917831","doi":"10.5087/dad.2013.211","title":"Annotation upon Annotation: Adding Signalling Information to a Corpus of Discourse Relations","year":2013,"lang":"en","type":"article","venue":"Dialogue & Discourse","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Annotation; Rhetorical question; Parsing; Computer science; Natural language processing; Artificial intelligence; Corpus linguistics; Linguistics; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002765632,0.0001730225,0.0001907322,0.0003484587,0.0001607433,0.0002858513,0.0005722105,0.00008807747,0.00002889076],"category_scores_gemma":[0.0002727414,0.0001589829,0.00006829094,0.0007068709,0.00005464024,0.0046949,0.0001376504,0.0001696828,0.0001961824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006978858,"about_ca_system_score_gemma":0.000109296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002249015,"about_ca_topic_score_gemma":0.00002413383,"domain_scores_codex":[0.9985624,0.00006533774,0.0004755192,0.0002407672,0.0003864537,0.0002695495],"domain_scores_gemma":[0.9986435,0.0001171069,0.0003408743,0.0003690051,0.0004111271,0.0001184585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003944592,0.000261452,0.001718672,0.0001344028,0.00006167075,0.00001127634,0.03341771,0.007389153,0.03477135,0.3927622,0.01069289,0.5187398],"study_design_scores_gemma":[0.003891584,0.001841664,0.03213746,0.002896896,0.0003125348,0.0001018879,0.009568351,0.4776159,0.1446264,0.3179081,0.004167668,0.004931541],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.103949,0.000259009,0.8916015,0.002366921,0.0002734502,0.0006304412,0.00002950125,0.0003638442,0.0005263444],"genre_scores_gemma":[0.7982851,0.000005039582,0.2011526,0.0002080742,0.00006182688,0.0001057471,0.0001334737,0.000009335032,0.00003888397],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6943361,"threshold_uncertainty_score":0.6483134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01066699860770908,"score_gpt":0.2763759844067075,"score_spread":0.2657089857989984,"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."}}