{"id":"W3045323648","doi":"10.5114/ppn.2020.96975","title":"Binary classification of pornographic and non-pornographic materials using the sAI 0.4 model and the modified sexACT database","year":2020,"lang":"pl","type":"article","venue":"Postępy Psychiatrii i Neurologii","topic":"Sexuality, Behavior, and Technology","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Binary number; Database; Binary classification; Chemistry; Computer science; Artificial intelligence; Support vector machine; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001670699,0.0007223166,0.0010747,0.0004658603,0.0006299481,0.0001264803,0.001098135,0.0007780063,0.00005210277],"category_scores_gemma":[0.0001487222,0.0004833035,0.0002286525,0.001367831,0.002947435,0.0001927914,0.0005767578,0.001177038,0.000009163355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000842345,"about_ca_system_score_gemma":0.00009940415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006787977,"about_ca_topic_score_gemma":0.00005611319,"domain_scores_codex":[0.994293,0.001684679,0.001392943,0.00144642,0.0003896255,0.0007933724],"domain_scores_gemma":[0.9961136,0.00056028,0.001162581,0.001814029,0.0001287882,0.0002207414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02092693,0.002860434,0.3582011,0.001142911,0.001420496,0.0001456266,0.01407214,0.0005321756,0.4630742,0.1304715,0.003312085,0.003840391],"study_design_scores_gemma":[0.03809233,0.008987643,0.7438003,0.000176093,0.008097954,0.001174709,0.009483376,0.1678563,0.002120351,0.01520744,0.001454452,0.003549053],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615135,0.004649492,0.0005487323,0.0289587,0.001463159,0.001901219,0.0006008224,0.00021059,0.0001537507],"genre_scores_gemma":[0.9920761,0.002375553,0.0002696456,0.004707079,0.0002728915,0.00008308474,0.00007239549,0.0001144305,0.00002882988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4609539,"threshold_uncertainty_score":0.999766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08520636405391403,"score_gpt":0.3293202032905186,"score_spread":0.2441138392366046,"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."}}