{"id":"W2152521636","doi":"10.1145/2207676.2208351","title":"The design space of opinion measurement interfaces","year":2012,"lang":"en","type":"article","venue":"","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ranking (information retrieval); Computer science; Space (punctuation); Set (abstract data type); Recall; Human–computer interaction; Rating scale; Interface (matter); The Internet; Information retrieval; User interface; World Wide Web; Mathematics; Psychology; Statistics; Cognitive psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.005392946,0.00005448228,0.00008620686,0.00007121746,0.0001006925,0.00003531668,0.0005015015,0.00005147683,0.0002586262],"category_scores_gemma":[0.001052589,0.00002560095,0.00003590321,0.0002257897,0.0001079286,0.0001456993,0.00008869648,0.00006914558,0.0003018751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001724434,"about_ca_system_score_gemma":0.00001926523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007139247,"about_ca_topic_score_gemma":0.000007563253,"domain_scores_codex":[0.9985314,0.0001535962,0.0002666374,0.000100454,0.0007918864,0.0001560193],"domain_scores_gemma":[0.9989127,0.0003171747,0.0001191128,0.0003883155,0.000221276,0.00004140813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001100859,0.0003621389,0.3287016,0.000002369777,0.00004083962,2.541549e-7,0.001575181,0.00004583204,0.02658545,0.1708998,0.2746487,0.1970277],"study_design_scores_gemma":[0.0004511678,0.000181731,0.3725884,0.00001901211,0.00001257727,0.000009538262,0.007519,0.0002224419,0.2890646,0.01607946,0.3136339,0.000218152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4302411,0.003061324,0.5351626,0.01595356,0.003328161,0.0004993702,0.000001824316,0.000228713,0.01152339],"genre_scores_gemma":[0.9956161,0.00002752545,0.003037603,0.00003206198,0.00001669881,0.000004846133,3.736045e-8,0.00000250343,0.001262578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.565375,"threshold_uncertainty_score":0.3880095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4065431518817881,"score_gpt":0.4242872738973248,"score_spread":0.01774412201553671,"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."}}