{"id":"W4405473276","doi":"10.2139/ssrn.5059947","title":"A Round-Up of Holiday Gifts from INFIDEOS","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Art; Business","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":[0.003519204,0.001062221,0.001063603,0.001368197,0.01821662,0.00797926,0.001452296,0.005042657,0.1273382],"category_scores_gemma":[0.01328596,0.0007208068,0.0009544084,0.001015095,0.002122754,0.004325885,0.009620558,0.01116156,0.03696608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0026601,"about_ca_system_score_gemma":0.002666564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005157298,"about_ca_topic_score_gemma":0.02056277,"domain_scores_codex":[0.9979418,0.0004752756,0.00004367949,0.0002498992,0.0006211145,0.0006682255],"domain_scores_gemma":[0.9856208,0.001554351,0.0003397395,0.001029692,0.001893747,0.009561517],"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":[0.0009586577,0.0003389952,0.001527843,0.0001044288,0.00002787889,0.001880918,0.003439663,0.0001827642,0.001018746,0.004168123,0.9552789,0.03107313],"study_design_scores_gemma":[0.00007758433,0.0001889081,0.004366419,0.00008059596,0.000006643944,0.0002916974,0.008804437,0.0001743539,0.0003125322,0.001941744,0.983704,0.00005113614],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1225344,0.007008476,0.006936708,0.2742809,0.2319105,0.001287643,0.008780244,0.004195371,0.3430657],"genre_scores_gemma":[0.1764192,0.001690037,0.005443829,0.03638472,0.02210374,0.0007143008,0.003521994,0.003347883,0.7503743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1273382,"threshold_uncertainty_score":0.4259886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250759179997475,"score_gpt":0.2845945428031722,"score_spread":0.2720869510031975,"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."}}