{"id":"W4239100792","doi":"10.1145/1082983.1082968","title":"xTAO","year":2005,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Modeling language; Software engineering; Extensibility; XML; Context (archaeology); Set (abstract data type); Human–computer interaction; Programming language; Systems engineering; Software; World Wide Web; Engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0001671242,0.0001728544,0.0001550049,0.000115595,0.00007074879,0.0001082805,0.0008435128,0.00007893673,0.00003890794],"category_scores_gemma":[0.01847114,0.0001705299,0.00007110954,0.0002386713,0.000006559068,0.0005769976,0.0002196613,0.0001198989,0.0003127062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000055766,"about_ca_system_score_gemma":0.00002094039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003027095,"about_ca_topic_score_gemma":0.000006381494,"domain_scores_codex":[0.9989089,0.00001305865,0.0002277753,0.000311388,0.0002346584,0.000304192],"domain_scores_gemma":[0.9925713,0.006429901,0.0000584465,0.0007866875,0.00004945644,0.0001042039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008133846,0.0002877899,0.5614991,0.0003245722,0.000144016,0.00005169706,0.004551398,0.05418751,0.02643907,0.01638615,0.01712804,0.3189925],"study_design_scores_gemma":[0.0013386,0.0001360671,0.6756649,0.0002911125,0.00002584569,0.00009274674,0.000008248745,0.06656538,0.05277741,0.00009071774,0.2012203,0.001788594],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.16565,0.0005347288,0.8300735,0.0008322684,0.000870549,0.0001856559,0.000004088871,0.001840271,0.000008940448],"genre_scores_gemma":[0.7889971,0.000005261995,0.2104039,0.0001346035,0.0002826974,0.00001632384,0.000004342659,0.00001776449,0.0001379611],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6233472,"threshold_uncertainty_score":0.9897967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597472109984308,"score_gpt":0.2266819340784866,"score_spread":0.2107072129786435,"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."}}