{"id":"W2137366722","doi":"10.1109/ipcc.1996.552599","title":"Using technology to tailor electronic information to users","year":2002,"lang":"en","type":"article","venue":"","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Hyperlink; Computer science; Documentation; World Wide Web; Field (mathematics); Multimedia; Web page","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003769265,0.0005020328,0.0002298917,0.001719683,0.0007092684,0.003806917,0.0008102256,0.001252773,0.004184477],"category_scores_gemma":[0.01500922,0.0003953454,0.0002395146,0.00128911,0.001358793,0.007568812,0.002088886,0.0006149834,0.001936314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007628895,"about_ca_system_score_gemma":0.0009444894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001196395,"about_ca_topic_score_gemma":0.001856272,"domain_scores_codex":[0.9971284,0.001456248,0.0001683075,0.0002780581,0.0007130182,0.0002559569],"domain_scores_gemma":[0.9911622,0.005821981,0.000562122,0.00130119,0.0009152376,0.0002373926],"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":[0.0003600666,0.0007146317,0.03348091,0.0006641338,0.0000529583,0.0008057514,0.02132355,0.003089136,0.05646354,0.03321818,0.008162055,0.8416651],"study_design_scores_gemma":[0.0004036262,0.004000263,0.07115781,0.00121388,0.000322848,0.004763573,0.04127587,0.03373385,0.1406405,0.07999735,0.6221204,0.0003699762],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6386704,0.0006579238,0.2322153,0.002089839,0.00007642264,0.0009652977,0.0001324846,0.003673298,0.121519],"genre_scores_gemma":[0.7821206,0.001079655,0.190472,0.0007284469,0.00006391948,0.0006577606,0.0002800134,0.0004749801,0.02412257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004184477,"threshold_uncertainty_score":0.019934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0450588412919157,"score_gpt":0.3722662208181675,"score_spread":0.3272073795262518,"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."}}