{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01059235,0.0007099583,0.000591487,0.0008987769,0.0005156248,0.003469615,0.0007376606,0.001703134,0.003875547],"category_scores_gemma":[0.05608338,0.0005313762,0.0007900007,0.0005877057,0.0004258521,0.003730208,0.0009033203,0.00131411,0.001148984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004546279,"about_ca_system_score_gemma":0.0006396113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002076975,"about_ca_topic_score_gemma":0.003253927,"domain_scores_codex":[0.9939254,0.004007676,0.0005096979,0.0003885904,0.0009451573,0.0002234959],"domain_scores_gemma":[0.9470017,0.04339446,0.002428652,0.003104805,0.003377363,0.0006930813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001056356,0.003461219,0.3273472,0.002333822,0.000632213,0.0005333647,0.03084014,0.01215814,0.03532969,0.005006182,0.003839263,0.5774624],"study_design_scores_gemma":[0.001012642,0.01783507,0.5184845,0.002054656,0.003098552,0.002470185,0.02776346,0.2810107,0.04850757,0.02008541,0.07663307,0.0010441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041722,0.000761207,0.08076359,0.001290708,0.00004766406,0.000400502,0.0001576969,0.0007437655,0.01166266],"genre_scores_gemma":[0.9266319,0.0004396252,0.0706651,0.0001744434,0.0000314961,0.0001130128,0.0001841963,0.00004137338,0.00171878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01059235,"threshold_uncertainty_score":0.05601841,"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."}}