{"id":"W6981196323","doi":"","title":"Duplicate Detection for Quality Assurance of Document Image Collections: Paper - iPRES 2012 - Digital Curation Institute, iSchool, Toronto","year":2012,"lang":"en","type":"article","venue":"Phaidra (Universität Wien)","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Robustness (evolution); Digital image; Image file formats; Document image processing; Quality assurance; Image processing; Automatic image annotation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003455974,0.0005889729,0.0009053033,0.004057543,0.00103693,0.002330557,0.00145379,0.001089529,0.005359967],"category_scores_gemma":[0.01275324,0.0004703507,0.0006878741,0.002188637,0.001397128,0.001812541,0.001888555,0.0006911861,0.002704673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121732,"about_ca_system_score_gemma":0.001616111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002300666,"about_ca_topic_score_gemma":0.003300732,"domain_scores_codex":[0.9958225,0.0007072106,0.0002088039,0.0006254307,0.002426174,0.0002098253],"domain_scores_gemma":[0.9897659,0.002640774,0.001018168,0.00340041,0.002939211,0.0002355382],"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":[0.0005755114,0.0001313197,0.01058631,0.0006772521,0.0001524715,0.0004130912,0.000557651,0.006114204,0.1523865,0.0030256,0.006979921,0.8184001],"study_design_scores_gemma":[0.00009168546,0.0007401327,0.03119074,0.0001993435,0.0003365303,0.005592218,0.0006040438,0.1592251,0.7603313,0.005862069,0.0356638,0.0001629657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.180882,0.005397735,0.8004443,0.000656561,0.0002520034,0.0004242409,0.000590957,0.005444635,0.005907644],"genre_scores_gemma":[0.4968236,0.002226081,0.4901529,0.0000964476,0.0001213794,0.000135114,0.001194356,0.000680679,0.008569478],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005359967,"threshold_uncertainty_score":0.01827717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01450686990541291,"score_gpt":0.2576323233897625,"score_spread":0.2431254534843496,"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."}}