{"id":"W7133098856","doi":"","title":"Natural Language Processing (NLP) For Ethical Artificial Intelligence (AI)","year":2025,"lang":"en","type":"dissertation","venue":"Trepo - Institutional Repository of Tampere University","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Latent Dirichlet allocation; Topic model; Perception; Ethical issues; Thematic analysis; Identification (biology); Natural language understanding; Software deployment","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004985,0.0001758708,0.0003329644,0.0002977906,0.001839451,0.00006296429,0.0003798259,0.0004711997,0.00003746604],"category_scores_gemma":[0.0007078568,0.0001956181,0.00036133,0.0004767039,0.0004080406,0.0002053723,0.00003572245,0.0005390488,0.000002153894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003841555,"about_ca_system_score_gemma":0.003558869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001840569,"about_ca_topic_score_gemma":0.003283786,"domain_scores_codex":[0.998224,0.0002316109,0.0003585606,0.000397442,0.0005982789,0.0001901693],"domain_scores_gemma":[0.9979924,0.0004478839,0.0003340387,0.0001266031,0.001016689,0.00008239125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001235032,0.0003765697,0.0001798672,0.0008239673,0.0004047061,0.000155892,0.02234916,0.002091921,0.002326597,0.7320989,0.0006071349,0.2373502],"study_design_scores_gemma":[0.001748911,0.0004949918,0.01400128,0.00574899,0.005605408,0.00006398903,0.2799845,0.06557408,0.03350094,0.09173564,0.4963829,0.005158381],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5389216,0.004238194,0.09881146,0.004520133,0.01002287,0.002110335,0.0002732222,0.0004912127,0.340611],"genre_scores_gemma":[0.9553823,0.00001752017,0.005398829,0.00005781025,0.0003720974,0.000002681905,0.000450957,0.000005979747,0.0383118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6403633,"threshold_uncertainty_score":0.99946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235354115550524,"score_gpt":0.3697557667082658,"score_spread":0.3374022255527606,"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."}}