{"id":"W3189241431","doi":"10.1063/5.0055812","title":"Brain-on-a-Chip: Characterizing the next generation of advanced <i>in vitro</i> platforms for modeling the central nervous system","year":2021,"lang":"en","type":"article","venue":"APL Bioengineering","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation; Israel Science Foundation; H2020 European Research Council; Teva Pharmaceutical Industries","keywords":"Neuroscience; Organ-on-a-chip; Computer science; Central nervous system; In vitro; Human brain; Chip; Microfluidics; Biology; Nanotechnology; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001099419,0.0004938396,0.0003414294,0.0003253794,0.0004144174,0.001810903,0.0009110582,0.000946547,0.0009115278],"category_scores_gemma":[0.0007321094,0.000187847,0.0003453778,0.0003609123,0.0006573398,0.001123166,0.000453289,0.0007616276,0.0005244121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005876046,"about_ca_system_score_gemma":0.0005726063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314674,"about_ca_topic_score_gemma":0.002839011,"domain_scores_codex":[0.9996036,0.00006924974,0.00002288659,0.00007853777,0.0001548641,0.00007091832],"domain_scores_gemma":[0.9996623,0.0001138579,0.00004449103,0.00005472036,0.00008808082,0.0000366559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004677231,0.00008899481,0.001498819,0.0003001995,0.00002015283,0.0001126716,0.0001513114,0.005730891,0.9653391,0.008349122,0.001442537,0.01691935],"study_design_scores_gemma":[0.000005686032,0.0002647288,0.002335629,0.00002950396,0.00002491803,0.0002433221,0.0001324383,0.02572588,0.9467553,0.001841548,0.02260203,0.00003897284],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3862019,0.006153818,0.5766224,0.00142925,0.0003537172,0.0004033648,0.001965072,0.001809764,0.02506064],"genre_scores_gemma":[0.5323225,0.004681306,0.4556423,0.0006493151,0.00007739847,0.0003926563,0.001576982,0.0002359534,0.004421632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001810903,"threshold_uncertainty_score":0.005814373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04514460025395958,"score_gpt":0.2551290574853595,"score_spread":0.2099844572313999,"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."}}