{"id":"W3140208587","doi":"10.1101/2021.03.26.437121","title":"High content 3D imaging method for quantitative characterization of organoid development and phenotype","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Organoid; Multicellular organism; Embryonic stem cell; High-content screening; Live cell imaging; Biology; Computer science; Computational biology; Cell biology; Cell","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":[0.0007254799,0.0006186406,0.0004510936,0.001935322,0.0003323298,0.0009448188,0.000700996,0.0008034777,0.003599891],"category_scores_gemma":[0.0009883628,0.0005550491,0.0005062282,0.0009825793,0.0004550302,0.0005233527,0.000680057,0.001026845,0.001709684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006204587,"about_ca_system_score_gemma":0.0005630422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009968755,"about_ca_topic_score_gemma":0.001443387,"domain_scores_codex":[0.9993467,0.00007823714,0.00004276865,0.0001437624,0.0003534453,0.00003506243],"domain_scores_gemma":[0.9989645,0.0003694081,0.0001330807,0.0002564659,0.0002297536,0.00004667393],"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":[0.00005507665,0.00003474177,0.0008201784,0.0001141184,0.00002489545,0.0000684769,0.00006170834,0.005804803,0.9539673,0.001961119,0.001338684,0.03574902],"study_design_scores_gemma":[0.00001019335,0.00003820518,0.005014838,0.00001973145,0.00002790689,0.0003337491,0.00003363226,0.1771989,0.8055246,0.001360071,0.0103745,0.00006371596],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0293858,0.0002811736,0.9634075,0.0001056785,0.00005985699,0.00008138632,0.001238662,0.003528945,0.00191107],"genre_scores_gemma":[0.1137004,0.0003657345,0.8813363,0.00009747159,0.00003240393,0.0003661437,0.001221088,0.0007771851,0.002103392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003599891,"threshold_uncertainty_score":0.01204282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02862145894529112,"score_gpt":0.2626174709593941,"score_spread":0.233996012014103,"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."}}