{"id":"W3128050366","doi":"10.31219/osf.io/3vy69","title":"Appreciating diversity of goals in computational neuroscience","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Diversity (politics); Computational neuroscience; Field (mathematics); Computer science; Computational model; Quality (philosophy); Management science; Psychology; Cognitive science; Data science; Sociology; Epistemology; Artificial intelligence; Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.1100272,0.0009142255,0.001387141,0.007789067,0.007540918,0.02124697,0.002813204,0.005547199,0.001356519],"category_scores_gemma":[0.1935098,0.0009005239,0.001062499,0.00402073,0.0403075,0.03911288,0.02063429,0.009988308,0.0002959264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004492996,"about_ca_system_score_gemma":0.004814475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00106922,"about_ca_topic_score_gemma":0.001321668,"domain_scores_codex":[0.9192701,0.05842807,0.004104339,0.004332659,0.01158229,0.002282528],"domain_scores_gemma":[0.771615,0.1721992,0.01104064,0.02168166,0.01608896,0.007374586],"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":[0.00009613014,0.00007756517,0.01130376,0.000361798,0.0001231754,0.0001713243,0.02339723,0.003185862,0.0006750824,0.9197576,0.00294187,0.03790864],"study_design_scores_gemma":[0.00001406548,0.00002429154,0.001623656,0.0002050843,0.00002066198,0.0001395873,0.006405091,0.003051711,0.0003060095,0.9779564,0.01022329,0.00003023292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.3048959,0.01816171,0.3391848,0.2219228,0.0009031251,0.0001863251,0.0001903865,0.0003660056,0.1141889],"genre_scores_gemma":[0.9498939,0.002070946,0.04315044,0.003635941,0.0002563307,0.0001332915,0.00006206855,0.0001273661,0.0006697351],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.1100272,"threshold_uncertainty_score":0.5818863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0973407855313691,"score_gpt":0.3007026361244631,"score_spread":0.203361850593094,"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."}}