{"id":"W4391682754","doi":"10.1016/j.neuron.2024.01.016","title":"Data science opportunities of large language models for neuroscience and biomedicine","year":2024,"lang":"en","type":"article","venue":"Neuron","topic":"Topic Modeling","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital","funders":"","keywords":"Biomedicine; Cognitive reframing; Cognitive science; Cognitive neuroscience; Neuroscience; Computational neuroscience; Cognition; Computer science; Psychology; Data science; Biology; Bioinformatics","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":[],"consensus_categories":[],"category_scores_codex":[0.02616977,0.001705195,0.001787852,0.003213821,0.001301515,0.008556397,0.002956068,0.004046661,0.004972469],"category_scores_gemma":[0.06853156,0.001123231,0.002066638,0.002830576,0.006287324,0.02518071,0.006817065,0.01489305,0.002028232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002919663,"about_ca_system_score_gemma":0.00281863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001905583,"about_ca_topic_score_gemma":0.002032132,"domain_scores_codex":[0.9935589,0.004416391,0.0002615021,0.0007113811,0.0009183752,0.0001333899],"domain_scores_gemma":[0.9162349,0.07242248,0.0009579288,0.006998332,0.002272766,0.001113633],"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":[0.0000866743,0.00006836958,0.001187042,0.0004419842,0.0001191358,0.000110843,0.0006236254,0.009206221,0.0006330044,0.9090922,0.01667691,0.06175401],"study_design_scores_gemma":[0.00001112391,0.00001985378,0.0001374455,0.0001415538,0.00001355554,0.00005042443,0.00008906865,0.03965177,0.0001989824,0.9353618,0.02429595,0.00002849027],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.004100155,0.03014718,0.8547006,0.09952065,0.001317926,0.000101042,0.001362454,0.001112558,0.007637408],"genre_scores_gemma":[0.1945682,0.04726018,0.7214373,0.01560407,0.01240231,0.001048127,0.002427375,0.0009480531,0.004304309],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02616977,"threshold_uncertainty_score":0.1384007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1726156762272152,"score_gpt":0.3524486334844527,"score_spread":0.1798329572572375,"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."}}