{"id":"W4404336935","doi":"10.1038/d41586-024-03679-6","title":"How AI is reshaping science and society","year":2024,"lang":"en","type":"article","venue":"Nature","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Engineering ethics; Political science; Data science; Computer science; 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.006405878,0.0005951741,0.0005793008,0.002534811,0.003974729,0.01083747,0.001544746,0.005107021,0.01528541],"category_scores_gemma":[0.01289677,0.0003930032,0.0006009555,0.002091396,0.02638082,0.0231385,0.00511103,0.006324039,0.003175474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003556525,"about_ca_system_score_gemma":0.005552226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006732447,"about_ca_topic_score_gemma":0.004543262,"domain_scores_codex":[0.9956191,0.001821516,0.0001406437,0.0004915959,0.001408577,0.0005184815],"domain_scores_gemma":[0.9882384,0.005312833,0.0005537868,0.002897504,0.001766155,0.001231265],"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":[0.00001985444,0.00003097019,0.0004186673,0.0001164046,0.00004196753,0.00007016953,0.001854574,0.0009081314,0.0003323183,0.9458685,0.02130312,0.02903523],"study_design_scores_gemma":[0.000005243417,0.0000076191,0.0002179427,0.00005474485,0.000007864991,0.00004305701,0.0008533778,0.0004951691,0.0001681725,0.8688523,0.1292817,0.00001275079],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01631871,0.02302775,0.05287967,0.3201215,0.009047025,0.00007023242,0.0002867788,0.0008113883,0.577437],"genre_scores_gemma":[0.8226067,0.0168265,0.02539759,0.03805521,0.006710424,0.0002163558,0.0002973702,0.0006953424,0.08919451],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9960253,"threshold_uncertainty_score":0.05113477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03498055300004582,"score_gpt":0.3007944454755449,"score_spread":0.2658138924754991,"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."}}