{"id":"W2021026569","doi":"10.1068/p5249","title":"An Information Theory Analysis of Visual Complexity and Dissimilarity","year":2006,"lang":"en","type":"article","venue":"Perception","topic":"University-Industry-Government Innovation Models","field":"Business, Management and Accounting","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Bitmap; Computational complexity theory; Overlay; Artificial intelligence; Image (mathematics); Computer science; Simple (philosophy); Pattern recognition (psychology); Set (abstract data type); Mathematics; Computer vision; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002623555,0.00006591454,0.0001053422,0.0003646331,0.000107063,0.0000939488,0.00005942863,0.00007514985,0.0006134202],"category_scores_gemma":[0.000009754312,0.0000686077,0.00003220596,0.0006223249,0.00005877573,0.002926836,0.00003878457,0.00007659717,0.00001054788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003884946,"about_ca_system_score_gemma":0.000003577615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007381699,"about_ca_topic_score_gemma":0.0001136009,"domain_scores_codex":[0.9994634,0.00001185533,0.0001668477,0.00008766972,0.0001971665,0.00007305931],"domain_scores_gemma":[0.9996079,0.00000736005,0.000169896,0.00009205048,0.0001179484,0.000004877922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008857006,0.0002407985,0.7482872,0.00006343234,0.00009418344,2.75672e-7,0.0002594173,0.002596308,0.004393273,0.2342984,0.0004252084,0.009252923],"study_design_scores_gemma":[0.0001472167,0.000005414165,0.8635745,0.000002569861,0.0001978704,6.026227e-8,0.0006720643,0.1310291,0.000009329665,0.003757963,0.0005323387,0.00007150048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613019,4.83832e-7,0.03106558,0.000113809,0.00002169747,0.00006792993,0.00001136449,0.00004176872,0.007375514],"genre_scores_gemma":[0.9988412,5.089285e-7,0.0002302322,0.0002945239,0.00009214252,7.62295e-7,0.0005001927,0.000002706466,0.00003775941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2305405,"threshold_uncertainty_score":0.6716521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251503024852034,"score_gpt":0.2527816649953738,"score_spread":0.2302666347468535,"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."}}