{"id":"W2970420303","doi":"10.32470/ccn.2019.1424-0","title":"Visualizing Representational Dynamics with Multidimensional Scaling Alignment","year":2019,"lang":"en","type":"article","venue":"2019 Conference on Cognitive Computational Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Dynamics (music); Multidimensional scaling; Scaling; Visualization; Theoretical computer science; Human–computer interaction; Artificial intelligence; Machine learning; Mathematics; Physics; Geometry","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":[0.0005141534,0.0006197084,0.0003160404,0.001701605,0.0003574839,0.001592378,0.000363974,0.0004274397,0.003996744],"category_scores_gemma":[0.002353144,0.0003175657,0.0005547175,0.001270402,0.0005026984,0.001810047,0.001260906,0.0008754439,0.000458086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003317543,"about_ca_system_score_gemma":0.0004820849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009643648,"about_ca_topic_score_gemma":0.0008924961,"domain_scores_codex":[0.9998072,0.0000486583,0.00001591976,0.00005464548,0.00005072325,0.0000227715],"domain_scores_gemma":[0.999479,0.0001761953,0.00009968477,0.0001032069,0.00009396131,0.00004794801],"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":[0.000473786,0.0001153346,0.007741872,0.0006378891,0.0002477381,0.00064715,0.002787805,0.144448,0.3199267,0.1212242,0.009981047,0.3917685],"study_design_scores_gemma":[0.00002519398,0.00007217882,0.008661726,0.00004587335,0.00002715631,0.0002650889,0.000454777,0.8799872,0.02543074,0.07570179,0.009250226,0.0000778891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07483247,0.0002678209,0.9200993,0.000429831,0.00006517234,0.00005964574,0.0005659165,0.001746334,0.001933501],"genre_scores_gemma":[0.4700967,0.0004423589,0.5272152,0.00006297752,0.00005726463,0.0001586501,0.000621779,0.0004697363,0.0008753621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003996744,"threshold_uncertainty_score":0.01337039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05745793673580415,"score_gpt":0.3213291460818171,"score_spread":0.263871209346013,"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."}}