{"id":"W2140061837","doi":"10.16995/dscn.253","title":"Toward Next Generation Text Analysis Tools: The Text Analysis Markup Language (TAML)","year":2005,"lang":"en","type":"article","venue":"Digital Studies / Le champ numérique","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Markup language; Computer science; Interoperability; Standardization; World Wide Web; Vocabulary; Linguistics; XML","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01806644,0.0008788866,0.0009099992,0.003209803,0.001154482,0.008604689,0.003069878,0.001749476,0.01802435],"category_scores_gemma":[0.0553797,0.0007345949,0.001001987,0.002111748,0.001750783,0.01529833,0.003727432,0.002961649,0.02115849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001233067,"about_ca_system_score_gemma":0.00357541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009306352,"about_ca_topic_score_gemma":0.0008754581,"domain_scores_codex":[0.9930321,0.003162756,0.0009871358,0.0008963492,0.001661094,0.000260497],"domain_scores_gemma":[0.9268777,0.03416735,0.004397001,0.01198754,0.01973223,0.002838087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003802709,0.0001917803,0.00314807,0.001692874,0.00006964733,0.0003148184,0.002112745,0.0008430285,0.03486337,0.1249069,0.0967388,0.7347378],"study_design_scores_gemma":[0.00008944813,0.0002605502,0.001626972,0.001776604,0.0001329934,0.0008161377,0.001448296,0.03516026,0.0808196,0.1067009,0.7709618,0.0002063688],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005113865,0.001081128,0.9508052,0.01053968,0.000678018,0.0002517549,0.002230221,0.01989245,0.009407742],"genre_scores_gemma":[0.03504977,0.001339438,0.9294788,0.002423587,0.0005694105,0.0003885774,0.005944395,0.005543096,0.01926294],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01806644,"threshold_uncertainty_score":0.09554559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05723028432510359,"score_gpt":0.2995974005432397,"score_spread":0.2423671162181362,"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."}}