{"id":"W3174843313","doi":"10.21467/proceedings.115.22","title":"Instagram Image Filtration with Computer Vision","year":2021,"lang":"en","type":"article","venue":"AIJR Proceedings","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Computer science; Upload; Face (sociological concept); Filter (signal processing); Information retrieval; Image (mathematics); Social media; Computer vision; Artificial intelligence; World Wide Web","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":[0.00009877412,0.00009684441,0.0001112783,0.00007209444,0.0001064668,0.0005100096,0.0001984817,0.00003666758,0.00005599307],"category_scores_gemma":[0.00001229221,0.00007907722,0.0000483004,0.0006627101,0.00002636686,0.001066905,0.00009150047,0.00009067568,0.0001228644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001826549,"about_ca_system_score_gemma":0.00004271813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003852452,"about_ca_topic_score_gemma":0.000004048067,"domain_scores_codex":[0.9991355,0.000006455461,0.0001233813,0.0003319315,0.0002341991,0.0001685366],"domain_scores_gemma":[0.9993522,0.00001268501,0.00005702483,0.00010651,0.0003991208,0.00007251062],"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":[0.00003250314,0.0007401151,0.003151638,0.0002274057,0.0001952762,0.000222714,0.00357762,0.0000581963,0.1455851,0.09141703,0.05156042,0.7032319],"study_design_scores_gemma":[0.002431138,0.00119208,0.01014647,0.0004281939,0.00009721025,0.0006978798,0.0008133443,0.6491312,0.259568,0.006025775,0.06803497,0.001433742],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0883274,0.00002760555,0.8946559,0.004851561,0.00009790645,0.00008998186,0.000001239847,0.0003105596,0.01163779],"genre_scores_gemma":[0.6925448,0.0000258075,0.3049819,0.001576847,0.00009662769,0.000009754883,0.00001288784,0.000009704107,0.000741713],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7017982,"threshold_uncertainty_score":0.4918034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00626581584672745,"score_gpt":0.2213691586688235,"score_spread":0.2151033428220961,"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."}}