{"id":"W7147000236","doi":"10.1145/3769872.3769875","title":"Exploring Feedforward in Data Physicalization Authoring Tools: Supporting Design Exploration Before Fabrication","year":2025,"lang":"","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Feed forward; Representation (politics); Simple (philosophy); Key (lock); Design elements and principles; Design methods; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002735632,0.001535153,0.0004720258,0.000792336,0.000610361,0.002723366,0.001809521,0.00129197,0.008190725],"category_scores_gemma":[0.01917977,0.0008223347,0.0007516852,0.0003502834,0.001865116,0.005202757,0.003105936,0.001406555,0.001127302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004629207,"about_ca_system_score_gemma":0.0007155719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003041603,"about_ca_topic_score_gemma":0.0007365068,"domain_scores_codex":[0.9987331,0.0004753704,0.00008345729,0.000249542,0.0003573811,0.0001010705],"domain_scores_gemma":[0.9862962,0.009913194,0.0006011603,0.002277763,0.0006568096,0.0002549192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008439913,0.0006294043,0.0110505,0.003426033,0.0001310788,0.002289674,0.03656451,0.08064956,0.3123268,0.07754003,0.007549478,0.4669989],"study_design_scores_gemma":[0.0002678742,0.001701742,0.007408552,0.001102668,0.0001948065,0.00223301,0.007549219,0.3926812,0.2700319,0.155002,0.1613809,0.0004461032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09690262,0.0003209437,0.8891853,0.000415923,0.00007713433,0.0002180207,0.0001661308,0.005638196,0.007075788],"genre_scores_gemma":[0.5082458,0.0002501203,0.486726,0.0001742506,0.00001800351,0.0003619602,0.0002053859,0.001173022,0.002845414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008190725,"threshold_uncertainty_score":0.02740067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4187301826371804,"score_gpt":0.3915950874998285,"score_spread":0.02713509513735185,"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."}}