{"id":"W4368346848","doi":"10.22541/au.168323192.20543041/v1","title":"AI Usage Cards: Responsibly Reporting AI-generated Content","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Niedersächsische Ministerium für Wissenschaft und Kultur","keywords":"Computer science; Transparency (behavior); Accountability; Header; Artificial intelligence; Work (physics); Key (lock); Data science; World Wide Web; Computer security; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05319048,0.001677188,0.000922185,0.008592648,0.003263251,0.0177296,0.004075857,0.004841464,0.01591776],"category_scores_gemma":[0.138315,0.001608883,0.00123199,0.004518439,0.007234106,0.02388584,0.01206886,0.005311928,0.01041852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004623759,"about_ca_system_score_gemma":0.008547886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007448486,"about_ca_topic_score_gemma":0.003788267,"domain_scores_codex":[0.935521,0.03670946,0.00991526,0.003230294,0.01270329,0.001920637],"domain_scores_gemma":[0.8331953,0.06187325,0.01394231,0.05993264,0.02674423,0.004312237],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006485374,0.0004298323,0.01227576,0.0007566413,0.00008719475,0.0006773084,0.01190946,0.008507816,0.004889776,0.587586,0.08699732,0.2852343],"study_design_scores_gemma":[0.0001763667,0.0004469281,0.00427191,0.001643797,0.0001203867,0.001082683,0.005112924,0.1014469,0.02901447,0.2162358,0.6397662,0.0006816945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0148075,0.0002492254,0.8830331,0.005515733,0.0008286783,0.004204968,0.002926075,0.02453117,0.06390354],"genre_scores_gemma":[0.1847485,0.0005673288,0.7736529,0.001482086,0.0003222301,0.003721645,0.003933287,0.002810168,0.02876191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9468095,"threshold_uncertainty_score":0.2813016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5977607630186599,"score_gpt":0.5172874066978922,"score_spread":0.08047335632076769,"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."}}