{"id":"W4234778484","doi":"10.1145/1030397","title":"Proceedings of the 2004 ACM symposium on Document engineering","year":2004,"lang":"en","type":"paratext","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gratitude; Presentation (obstetrics); Computer science; IBM; Library science; Variety (cybernetics); World Wide Web; Artificial intelligence; Psychology","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":[0.0001590212,0.0002374734,0.0002964098,0.0001612092,0.00005607784,0.0002019759,0.003270596,0.0001273359,0.0001337348],"category_scores_gemma":[0.00003816531,0.000148772,0.0001831701,0.0005365002,0.00002129447,0.0001897516,0.0008520315,0.000270529,0.0007349342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001129412,"about_ca_system_score_gemma":0.0001295179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009500689,"about_ca_topic_score_gemma":9.335974e-7,"domain_scores_codex":[0.9985906,0.00000440013,0.000273565,0.0004527876,0.0004352596,0.0002433267],"domain_scores_gemma":[0.998767,0.00003395817,0.0001820371,0.0008756691,0.00008486441,0.00005652798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003172354,0.0001070626,0.0000168084,0.0003819479,0.0002804327,0.000001931051,0.000532223,0.0250992,0.003701765,0.04611976,0.9225821,0.001173619],"study_design_scores_gemma":[0.0009514066,0.0004369335,0.0001506622,0.003896914,0.0002410417,0.00002893709,0.00008336582,0.009936194,0.1374422,0.0008244139,0.844183,0.001824883],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005392136,0.001083237,0.05617522,0.01602472,0.008565151,0.00107589,0.0001286835,0.0005055933,0.9110494],"genre_scores_gemma":[0.103759,0.0003697463,0.05430902,0.001036895,0.0009301606,0.00007959457,0.00005202145,0.00008896329,0.8393747],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1337404,"threshold_uncertainty_score":0.9446337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008252235018341946,"score_gpt":0.2211615517570888,"score_spread":0.2129093167387469,"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."}}