{"id":"W6955215979","doi":"10.58079/ni4k","title":"Identification d'images - test de TinEye sur PhotosNormandie","year":2008,"lang":"fr","type":"article","venue":"Industrias Culturais (Universidade de Coimbra)","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Pattern recognition (psychology); Test (biology); Relation (database)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004938351,0.0004608651,0.0003939632,0.0003733452,0.0006068907,0.0006702244,0.00120966,0.0007012833,0.0002248667],"category_scores_gemma":[0.001554587,0.0005428172,0.0002437829,0.001913157,0.0006619635,0.004599503,0.0003350445,0.0009262383,0.0009246639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009966214,"about_ca_system_score_gemma":0.0009962899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00174227,"about_ca_topic_score_gemma":0.000156042,"domain_scores_codex":[0.9967745,0.0002054483,0.0004788415,0.0008114844,0.0006754555,0.001054249],"domain_scores_gemma":[0.9972163,0.0004598097,0.0004481015,0.0007588855,0.0005200419,0.0005967944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001107378,0.001240678,0.007427358,0.0001727547,0.0003439321,0.003323519,0.01236087,0.0006636077,0.08613528,0.009942742,0.728853,0.1494256],"study_design_scores_gemma":[0.00436319,0.0008000935,0.4123657,0.0005936637,0.0002721762,0.006861638,0.001929538,0.0164951,0.1671539,0.0008126454,0.3863424,0.002009956],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7385211,0.001996322,0.04943736,0.07561606,0.01004296,0.00176318,0.000563113,0.001611178,0.1204487],"genre_scores_gemma":[0.8181332,0.0002407922,0.001474659,0.0004343491,0.0006379792,0.00001767177,0.00006401508,0.00004590919,0.1789514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4049383,"threshold_uncertainty_score":0.9998533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03549357073650337,"score_gpt":0.2320754134328287,"score_spread":0.1965818426963253,"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."}}