{"id":"W4393969098","doi":"10.48550/arxiv.2404.02743","title":"IEEE VIS Workshop on Visualization for Climate Action and Sustainability","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Visualization; Sustainability; Visual analytics; Action (physics); Context (archaeology); Storytelling; Engineering ethics; Computer science; Data science; Knowledge management; Public relations; Political science; Engineering; Geography; Ecology","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":[0.009836769,0.0015805,0.0009853475,0.001935464,0.001401949,0.008348894,0.002483373,0.002755826,0.03705705],"category_scores_gemma":[0.01045486,0.0006518063,0.002174472,0.002037653,0.001451327,0.005747175,0.005644967,0.005770294,0.01169448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001659253,"about_ca_system_score_gemma":0.002581313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004838026,"about_ca_topic_score_gemma":0.005280898,"domain_scores_codex":[0.9961035,0.001390269,0.0001598675,0.0006073089,0.001297878,0.0004412493],"domain_scores_gemma":[0.9930283,0.001913165,0.0001343567,0.001201458,0.002300918,0.001421726],"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":[0.0003316553,0.0002518932,0.000722034,0.0004531207,0.0001808435,0.0004559939,0.001358815,0.00408084,0.007192871,0.05146514,0.7194185,0.2140882],"study_design_scores_gemma":[0.00003292908,0.00008156984,0.0006748796,0.0003291167,0.00003587491,0.0002275752,0.0004006998,0.005568446,0.00310817,0.02901085,0.9604837,0.00004614295],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02101798,0.06199113,0.5388564,0.07331438,0.09153894,0.0007351893,0.005722363,0.01298664,0.1938369],"genre_scores_gemma":[0.151265,0.0547783,0.2780966,0.01052715,0.02775236,0.001107025,0.01864629,0.01029507,0.4475322],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03705705,"threshold_uncertainty_score":0.1239682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5175105578951946,"score_gpt":0.3957267954442801,"score_spread":0.1217837624509145,"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."}}