{"id":"W4414680536","doi":"10.33767/osf.io/tyfbm_v1","title":"Flirting Charts: Expressive Motion Design in Information Visualization Inspired by Animal Courtship Performances","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flirting; Motion (physics); Visualization; Courtship; Code (set theory); Choreography","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":[0.000617153,0.0009654357,0.0003875387,0.00126483,0.000535042,0.001768632,0.0009352339,0.0005371082,0.007285683],"category_scores_gemma":[0.003309115,0.0002991747,0.000675954,0.000961894,0.0009423291,0.001519032,0.001469253,0.000827684,0.001028545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004126742,"about_ca_system_score_gemma":0.0003753674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002199922,"about_ca_topic_score_gemma":0.003367579,"domain_scores_codex":[0.9997378,0.00008796868,0.00001524269,0.00006028013,0.0000652273,0.00003352741],"domain_scores_gemma":[0.9990165,0.0004986462,0.00007227129,0.0001526234,0.0001627878,0.00009705337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008665905,0.0001850113,0.007587111,0.001759102,0.0001700524,0.001207889,0.01028975,0.07621416,0.1834736,0.101046,0.04620199,0.5709988],"study_design_scores_gemma":[0.0001468354,0.0004927043,0.006106373,0.0004332376,0.0001479839,0.0007663381,0.002012866,0.6062533,0.1168291,0.08774509,0.1788148,0.000251341],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03792738,0.0006770892,0.9427842,0.0004699767,0.0001599361,0.000119893,0.001094626,0.01097782,0.005789145],"genre_scores_gemma":[0.3595146,0.0008719874,0.6294098,0.0001919753,0.00008401911,0.0002889825,0.001646519,0.003042625,0.004949556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007285683,"threshold_uncertainty_score":0.02437305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875751148281971,"score_gpt":0.2934940841533398,"score_spread":0.2747365726705201,"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."}}