{"id":"W4408365309","doi":"10.3390/electronics14061113","title":"Multitask Learning for Authenticity and Authorship Detection","year":2025,"lang":"en","type":"article","venue":"Electronics","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multi-task learning; Computer science; Artificial intelligence; Human–computer interaction; Data science; Natural language processing; Engineering; Task (project management); Systems engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005463291,0.001568915,0.001326423,0.00165218,0.001082696,0.001897493,0.002231227,0.002060503,0.002754743],"category_scores_gemma":[0.01306545,0.0004709339,0.001527644,0.001297311,0.001090289,0.003390721,0.003276824,0.003028422,0.002286207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197863,"about_ca_system_score_gemma":0.001371059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00206866,"about_ca_topic_score_gemma":0.003025393,"domain_scores_codex":[0.9965893,0.001651122,0.0001728365,0.0007554206,0.0005149586,0.0003162503],"domain_scores_gemma":[0.9930514,0.003360905,0.0006325798,0.001672889,0.0008787091,0.0004034006],"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":[0.001334652,0.001380569,0.01635031,0.0005986911,0.0004476648,0.000610774,0.0009511276,0.1796578,0.02133826,0.01645073,0.02250451,0.7383749],"study_design_scores_gemma":[0.00002060926,0.00009080493,0.001398194,0.00002047327,0.00003360581,0.00008004236,0.0001120558,0.9656076,0.003944031,0.02630522,0.002362343,0.00002497167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1355629,0.001466918,0.8504177,0.001747553,0.0003154127,0.000160741,0.0008028237,0.004402698,0.00512328],"genre_scores_gemma":[0.8593404,0.0002536873,0.1329325,0.0004639652,0.0003135752,0.000205617,0.001636338,0.0002097045,0.004644086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005463291,"threshold_uncertainty_score":0.02889299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830068670603032,"score_gpt":0.3311849632056816,"score_spread":0.3128842764996513,"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."}}