{"id":"W615032608","doi":"10.1007/978-3-319-07467-2_46","title":"Configuring the Webpage Content through Conditional Constraints and Preferences","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Web page; Personalization; Constraint (computer-aided design); Set (abstract data type); Content (measure theory); Preference; Web content; Information retrieval; Expressive power; World Wide Web; Theoretical computer science; Programming language; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005632861,0.0003380447,0.0003223043,0.0002104029,0.0003920383,0.0005943786,0.001153656,0.0001809575,0.0001227477],"category_scores_gemma":[0.00008460262,0.0002485133,0.00006597656,0.0001749134,0.00242507,0.0004071273,0.0004602514,0.0005346914,0.00002227174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008425235,"about_ca_system_score_gemma":0.0003143153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001410551,"about_ca_topic_score_gemma":0.00006729375,"domain_scores_codex":[0.997693,0.00005040256,0.0003933162,0.0009009083,0.0006129303,0.0003494237],"domain_scores_gemma":[0.9981992,0.0006761019,0.0002566592,0.0005727403,0.0001997273,0.00009554157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000002529483,0.000006602513,0.0001356482,0.00001880627,0.00001541237,0.00001263799,0.0007091976,0.006136021,0.00005665459,0.4063957,0.00002320346,0.5864876],"study_design_scores_gemma":[0.0009117528,0.0002152707,0.003852223,0.0005530713,0.0000237325,0.0005139347,0.000003449508,0.4640826,0.0009595857,0.52267,0.005072777,0.001141673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00009558035,0.0001677653,0.9872011,0.001882077,0.0008820486,0.0003423398,0.00001024889,0.00009477789,0.009324053],"genre_scores_gemma":[0.8692234,0.0001109099,0.1267312,0.00332002,0.0002582277,0.00001255028,0.00001206852,0.00001586419,0.0003157599],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8691278,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03434033797897846,"score_gpt":0.2412863982350816,"score_spread":0.2069460602561031,"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."}}