{"id":"W6902879252","doi":"10.7910/dvn/5hcppc","title":"Replication Data for: The multidimensional structure of risk: how dread and controllability shape attitudes toward artificial intelligence","year":2025,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Western University","funders":"","keywords":"Controllability; Replication (statistics); Key (lock); Work (physics); Applications of artificial intelligence; Outcome (game theory); Public opinion","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003729322,0.001795241,0.001252512,0.003689756,0.00130417,0.003086606,0.003220063,0.002143809,0.09562717],"category_scores_gemma":[0.02497993,0.0006962247,0.001456737,0.006089476,0.000619836,0.001823144,0.002836612,0.002650762,0.06821807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002301987,"about_ca_system_score_gemma":0.003874517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09648354,"about_ca_topic_score_gemma":0.1425941,"domain_scores_codex":[0.998086,0.0004565569,0.0002805701,0.0004313739,0.000455322,0.0002902152],"domain_scores_gemma":[0.9903859,0.002898233,0.0009706582,0.001710974,0.003438231,0.0005959828],"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":[0.00005616367,0.0000258524,0.002350311,0.0003729017,0.0000374358,0.00002460751,0.00004419099,0.0001803153,0.00003340483,0.0005341036,0.9946448,0.001695898],"study_design_scores_gemma":[0.001375792,0.00004227908,0.01927357,0.0006034093,0.0001001495,0.00009074913,0.0004646001,0.001075837,0.0002884494,0.00222085,0.9743904,0.00007385469],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004004893,0.00007394082,0.00009496579,0.0003201256,0.00006376298,0.00002492873,0.9978886,0.0001943031,0.0009388793],"genre_scores_gemma":[0.001690479,0.00006372394,0.0004035603,0.0001014002,0.00002140535,0.0002196457,0.9956185,0.0000738971,0.001807401],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09648354,"threshold_uncertainty_score":0.3199047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05759821796707477,"score_gpt":0.3241680717340072,"score_spread":0.2665698537669324,"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."}}