{"id":"W4321372906","doi":"10.3390/app13042706","title":"Improving User Experience with Recommender Systems by Informing the Design of Recommendation Messages","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Recommender system; Situational ethics; Computer science; Extant taxon; Transparency (behavior); Advice (programming); Product (mathematics); Perception; World Wide Web; Psychology; Social psychology; Computer security","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":[0.005168393,0.0001247731,0.0001868988,0.0002938959,0.0006391824,0.0002811147,0.001212825,0.00007687014,0.00008204688],"category_scores_gemma":[0.0002914067,0.00006434611,0.00002321529,0.002431459,0.000653833,0.0005014409,0.0001763235,0.0001374954,0.00007146379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001781349,"about_ca_system_score_gemma":0.00006866118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004894892,"about_ca_topic_score_gemma":0.000007074738,"domain_scores_codex":[0.9978253,0.0001055599,0.0004906511,0.0004131294,0.0008689893,0.0002964238],"domain_scores_gemma":[0.99795,0.001108217,0.0004156794,0.00038032,0.0001031545,0.00004261746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001403036,0.000196093,0.1371457,0.00002867343,0.00005709207,0.000005123372,0.02277165,0.01506944,0.1118415,0.04706002,0.1360413,0.5296431],"study_design_scores_gemma":[0.002801281,0.001086492,0.04368196,0.0001277979,0.00008315045,0.0000717781,0.6427206,0.09180287,0.1213482,0.008602702,0.08559529,0.002077858],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8413864,0.00004127386,0.1512215,0.003016927,0.00042204,0.0006995585,0.00001119832,0.0003111646,0.002889919],"genre_scores_gemma":[0.9977729,0.00001324788,0.001292082,0.0001624634,0.00001031811,0.0001188612,0.000002200149,0.000005878502,0.0006220833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.619949,"threshold_uncertainty_score":0.4916139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1608453554678385,"score_gpt":0.3738747597939989,"score_spread":0.2130294043261604,"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."}}