{"id":"W4403371077","doi":"10.19184/ejlh.v11i2.43512","title":"Analysing Discrimination based on Genetic Information","year":2024,"lang":"en","type":"article","venue":"Lentera Hukum","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science","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":[0.01273853,0.0002910749,0.0003868942,0.003390331,0.003220806,0.004495454,0.001124647,0.002094822,0.004094905],"category_scores_gemma":[0.0494146,0.000146264,0.000436736,0.005028242,0.01419523,0.004201992,0.005487874,0.002518291,0.0002636792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006137409,"about_ca_system_score_gemma":0.00434244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008027653,"about_ca_topic_score_gemma":0.007340867,"domain_scores_codex":[0.9813938,0.01156693,0.000490188,0.0009800931,0.004283342,0.001285699],"domain_scores_gemma":[0.9055476,0.07995585,0.008153328,0.002668701,0.002953464,0.0007209914],"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":[0.00008435894,0.0001285131,0.08201306,0.0004734774,0.00005410756,0.001512897,0.1839232,0.0009101631,0.0004880327,0.6541749,0.003708309,0.07252904],"study_design_scores_gemma":[0.00003562176,0.0001658967,0.1316108,0.002679975,0.0001066813,0.00182019,0.3148882,0.003692616,0.001351834,0.4335617,0.1099815,0.0001049909],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7792603,0.00463797,0.01934502,0.03011695,0.000257064,0.000134467,0.0002883513,0.00002462803,0.1659353],"genre_scores_gemma":[0.994522,0.0008362897,0.001766738,0.00116387,0.00004394843,0.00004502506,0.00005297352,0.000009173044,0.001560013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01273853,"threshold_uncertainty_score":0.06736857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009128101008679345,"score_gpt":0.2432785179633171,"score_spread":0.2341504169546378,"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."}}