{"id":"W4285267073","doi":"10.1109/jiot.2022.3181607","title":"PupilRec: Leveraging Pupil Morphology for Recommending on Smartphones","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Social Science Fund of China; National Natural Science Foundation of China","keywords":"Computer science; Pupil; Morphology (biology); Computer network","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":[0.001822268,0.0001647506,0.0003176212,0.0003733455,0.0002769627,0.0001911158,0.001544363,0.00004595996,0.00007695795],"category_scores_gemma":[0.00004096996,0.0001525405,0.0002269002,0.0001494565,0.00002142465,0.0005136481,0.000328039,0.0005891222,0.000003527217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002079874,"about_ca_system_score_gemma":0.00004583038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001024975,"about_ca_topic_score_gemma":6.757392e-7,"domain_scores_codex":[0.9982625,0.0001982687,0.00058233,0.0002950011,0.0003287972,0.0003330516],"domain_scores_gemma":[0.9986885,0.0002357613,0.0005998751,0.0002987201,0.00009292092,0.00008428509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003273287,0.0007065815,0.002164775,0.0001389736,0.0005162146,0.0003065937,0.02292725,0.0004946546,0.04997946,0.05702284,0.588574,0.2768413],"study_design_scores_gemma":[0.004039399,0.007097213,0.0004799341,0.0007350849,0.00005688285,0.01513802,0.001420932,0.09016556,0.3773199,0.0910461,0.4109331,0.001567802],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1041645,0.0001074308,0.8811134,0.004492534,0.007776981,0.0002219621,0.000003380474,0.0001344335,0.00198542],"genre_scores_gemma":[0.9562897,0.00001360511,0.04094862,0.001651215,0.0001860818,0.00005064591,0.000001109152,0.00002070759,0.0008383112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8521252,"threshold_uncertainty_score":0.6220421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04470289827238697,"score_gpt":0.2795395881361712,"score_spread":0.2348366898637843,"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."}}