{"id":"W7106565404","doi":"10.57760/sciencedb.31999","title":"How Consumer Happiness Travels Across Markets","year":2025,"lang":"en","type":"dataset","venue":"ScienceDB","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Happiness; Sample (material); Control (management); Panel data; Consumer behaviour; Data collection; Market research; Point (geometry)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009031115,0.0002042074,0.0002487108,0.001455044,0.000464254,0.002042649,0.0004645275,0.0005277485,0.01167287],"category_scores_gemma":[0.00625706,0.0001736786,0.0003615759,0.004869554,0.0002563572,0.001521669,0.0009899875,0.0008143752,0.004114489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214008,"about_ca_system_score_gemma":0.0006246548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03923279,"about_ca_topic_score_gemma":0.04890285,"domain_scores_codex":[0.9993013,0.0002705366,0.00005226073,0.000183484,0.0001104675,0.00008187028],"domain_scores_gemma":[0.9982283,0.0008164038,0.0002981097,0.0001629569,0.0003761834,0.0001181601],"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":[0.0003338889,0.0001926347,0.2898906,0.0008896068,0.0001570352,0.0002066306,0.004320303,0.003212549,0.000373695,0.01639745,0.6319367,0.0520888],"study_design_scores_gemma":[0.0000703949,0.00006511768,0.5805413,0.0004620577,0.00004561016,0.0001792108,0.009190903,0.004286677,0.0003137936,0.007368225,0.397386,0.00009087226],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2137367,0.0009942132,0.001746291,0.004118033,0.0001272106,0.0001259369,0.7560003,0.0001491311,0.02300218],"genre_scores_gemma":[0.3507341,0.001243937,0.002890068,0.0005676182,0.00008342003,0.0007078352,0.6346729,0.0001511771,0.008948887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03923279,"threshold_uncertainty_score":0.07800889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02258092156481136,"score_gpt":0.324202791652043,"score_spread":0.3016218700872316,"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."}}