{"id":"W2129174913","doi":"10.1017/s1351324908004683","title":"Industry Watch: Language technology, meet social networking","year":2008,"lang":"en","type":"article","venue":"Natural Language Engineering","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Thread (computing); World Wide Web; Quarter (Canadian coin); Language technology; Data science; Telecommunications; Artificial intelligence; Natural language; Programming language; Comprehension approach; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008997681,0.0002276997,0.0002040049,0.0001990703,0.00019593,0.00005210144,0.0009388284,0.0004469572,0.000009776328],"category_scores_gemma":[0.00001165639,0.0002038827,0.0000772761,0.001080254,0.00002499703,0.0002743748,0.0003513574,0.001299095,0.00001568411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000416579,"about_ca_system_score_gemma":0.00002226426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000072856,"about_ca_topic_score_gemma":0.0000343246,"domain_scores_codex":[0.9987024,0.00001679939,0.0001799403,0.0003441847,0.0002588926,0.0004977526],"domain_scores_gemma":[0.9994313,0.00004770768,0.00005614711,0.0003579555,0.00003432213,0.00007260021],"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":[0.00005713178,0.0002805288,0.008473924,0.0005428713,0.0006922266,0.008859359,0.25053,0.01411868,0.278813,0.04989563,0.005801849,0.3819348],"study_design_scores_gemma":[0.005658058,0.0003390803,0.01991548,0.0008962828,0.0001425324,0.004874455,0.01460564,0.5530086,0.2746674,0.0005567822,0.1182659,0.00706977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783779,0.00657872,0.008864458,0.00210099,0.00136132,0.000135762,0.000003239906,0.001661801,0.0009158491],"genre_scores_gemma":[0.9888495,0.000006507656,0.009447878,0.0005943178,0.0009246285,0.000009891718,0.000008695111,0.00002338924,0.0001352319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5388899,"threshold_uncertainty_score":0.8314096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004611272547601871,"score_gpt":0.209634801010973,"score_spread":0.2050235284633712,"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."}}