{"id":"W4237336490","doi":"10.32920/ryerson.14660730.v1","title":"Testing and Targeting a Mobile Application for Creatives","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Craft; Social media; Computer science; Test (biology); Internet privacy; World Wide Web; Multimedia; Visual arts","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":[0.008136818,0.0009315752,0.0004755335,0.001169779,0.0009968622,0.002714068,0.001810278,0.002834437,0.006037278],"category_scores_gemma":[0.0431379,0.0004908239,0.0006689401,0.000487896,0.001300492,0.00341076,0.002131111,0.001456836,0.003214464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000777353,"about_ca_system_score_gemma":0.0009335953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001502143,"about_ca_topic_score_gemma":0.001164373,"domain_scores_codex":[0.9913321,0.00466678,0.0005327435,0.0007893851,0.001912423,0.0007665966],"domain_scores_gemma":[0.9624155,0.02707518,0.0009090908,0.002918718,0.005384922,0.001296514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005696081,0.02130155,0.09957012,0.0042341,0.0002456512,0.006162325,0.0944527,0.00821151,0.2680404,0.01799777,0.01103829,0.4630495],"study_design_scores_gemma":[0.001991803,0.08534926,0.1565848,0.001769586,0.0008259769,0.006760588,0.0806516,0.1290454,0.3593724,0.01248543,0.1646055,0.0005577059],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448223,0.0001097276,0.03346159,0.0006892662,0.0001610606,0.002539705,0.000236273,0.001062899,0.01691712],"genre_scores_gemma":[0.9349848,0.0001237921,0.05109033,0.0005341517,0.0000464297,0.001833213,0.0003516914,0.0002635868,0.01077194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008136818,"threshold_uncertainty_score":0.04303217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03058217212005517,"score_gpt":0.3128543925945224,"score_spread":0.2822722204744672,"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."}}