{"id":"W4385399894","doi":"10.31219/osf.io/mpq32","title":"Enthusiastic and Grounded, Avoidant and Cautious: Understanding Public Receptivity to Data and Visualizations","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canada Research Chairs","keywords":"Openness to experience; Visualization; Qualitative property; Data visualization; Exploratory research; Qualitative research; Grounded theory; Information visualization; Public domain; Data science; Psychology; Social psychology; Computer science; Sociology; Geography; Social science; Data mining","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.02997199,0.0006154267,0.0005404441,0.002825992,0.005639959,0.0104516,0.001531669,0.002846202,0.002030401],"category_scores_gemma":[0.05822418,0.0007750752,0.0005827181,0.00150756,0.01761474,0.01242518,0.01033463,0.003701741,0.000284045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002345066,"about_ca_system_score_gemma":0.002076921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002992105,"about_ca_topic_score_gemma":0.002187589,"domain_scores_codex":[0.9763506,0.01911158,0.0005149283,0.001029084,0.001810475,0.001183436],"domain_scores_gemma":[0.9282098,0.06027307,0.004414038,0.00319248,0.002238855,0.00167184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003433532,0.00001595875,0.005650515,0.00008928612,0.000006905655,0.0002020915,0.9826797,0.0000381693,0.001079889,0.005666696,0.0001624553,0.004374121],"study_design_scores_gemma":[0.00001290187,0.00006221592,0.006746999,0.0003245359,0.00002200593,0.000370855,0.9635531,0.0007046153,0.001155251,0.01045428,0.01654352,0.00004987366],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.967648,0.0004150016,0.01573147,0.004185518,0.00005300315,0.00006828605,0.00004827889,0.00007748967,0.01177302],"genre_scores_gemma":[0.9975852,0.0001501084,0.001364068,0.0002968762,0.00001383784,0.0000439116,0.00002063661,0.00003739716,0.0004880798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02997199,"threshold_uncertainty_score":0.1585089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3155008879693996,"score_gpt":0.3843356647026099,"score_spread":0.06883477673321037,"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."}}