{"id":"W4403147008","doi":"","title":"Hard rules versus soft norms? Lessons of previous normative initiatives on AI and nanotechnology for quantum technologies","year":2023,"lang":"fr","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Normative; Nanotechnology; Quantum; Normative model of decision-making; Computer science; Engineering ethics; Engineering; Political science; Materials science; Physics; Quantum mechanics; Law","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.04189064,0.0006663523,0.001333645,0.003710343,0.007786701,0.01625391,0.003398419,0.009842897,0.008785787],"category_scores_gemma":[0.04515409,0.0003971709,0.0006324961,0.003070644,0.08636264,0.02295544,0.006824485,0.01407295,0.0007543992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01402945,"about_ca_system_score_gemma":0.01220386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01148151,"about_ca_topic_score_gemma":0.01256377,"domain_scores_codex":[0.9827766,0.009838351,0.0004790362,0.001519411,0.004127465,0.001259159],"domain_scores_gemma":[0.9219561,0.06094357,0.002075372,0.004144796,0.008207498,0.002672655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008639339,0.00001969815,0.00007379671,0.00003824199,0.000004046652,0.0000164383,0.002266377,0.0001437456,0.00002944495,0.9909008,0.001187139,0.005311623],"study_design_scores_gemma":[0.000006997979,0.000009558255,0.0001712953,0.0002515163,0.000003146113,0.00001670194,0.002531417,0.0002346796,0.000106966,0.9741884,0.02246744,0.00001190281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03703046,0.01917218,0.02497101,0.4690314,0.002496619,0.00006215664,0.00007910923,0.00007388898,0.4470831],"genre_scores_gemma":[0.9313604,0.01006901,0.006387613,0.03474336,0.002705772,0.0001781307,0.00004183689,0.0001881889,0.01432575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9922133,"threshold_uncertainty_score":0.2215415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05547811328225272,"score_gpt":0.3363403652095166,"score_spread":0.2808622519272639,"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."}}