{"id":"W4401745183","doi":"10.3389/fbinf.2024.1353807","title":"Design principles for molecular animation","year":2024,"lang":"en","type":"article","venue":"Frontiers in Bioinformatics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Animation; Function (biology); Computer science; Flexibility (engineering); Agency (philosophy); Visualization; Set (abstract data type); Design elements and principles; Molecular graphics; Human–computer interaction; Motion (physics); Data science; Nanotechnology; Computer graphics; Epistemology; Artificial intelligence; Computer graphics (images); Biology","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":[0.006252534,0.001560132,0.0007233587,0.001752537,0.002609106,0.005451487,0.003141514,0.003772848,0.02104493],"category_scores_gemma":[0.01509155,0.001243955,0.001819345,0.001009297,0.007153124,0.004979159,0.003910975,0.004790111,0.008187798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002411518,"about_ca_system_score_gemma":0.001975427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00154395,"about_ca_topic_score_gemma":0.001267726,"domain_scores_codex":[0.9955236,0.001769317,0.0003550574,0.0005718345,0.00149989,0.0002803284],"domain_scores_gemma":[0.9946347,0.002589063,0.0003279905,0.0009763407,0.001223241,0.0002485739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000242483,0.00001748717,0.0001011617,0.00020929,0.00001225989,0.00005771029,0.0004190749,0.00661146,0.001276592,0.9642655,0.005541031,0.02146425],"study_design_scores_gemma":[0.00007763663,0.00006731255,0.00009057756,0.0002718664,0.00002925669,0.0002834288,0.0001403001,0.04270166,0.003580293,0.6267141,0.32599,0.00005361182],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009011948,0.0008564572,0.9629395,0.002202147,0.0004701994,0.0002703261,0.0001091855,0.001210796,0.03104017],"genre_scores_gemma":[0.0522388,0.001465548,0.9190584,0.00122069,0.0002981841,0.002116297,0.0002274673,0.001027041,0.0223476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02104493,"threshold_uncertainty_score":0.07040232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492711352337584,"score_gpt":0.2827493998828617,"score_spread":0.2578222863594859,"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."}}