{"id":"W4312086499","doi":"10.1002/alz.068695","title":"Developing a bioprinted scaffold‐based model of neurodegeneration for high throughput screening in Drug Development","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"","keywords":"Scaffold; 3D cell culture; Drug discovery; Extracellular matrix; Induced pluripotent stem cell; Neurodegeneration; Progenitor cell; Microglia; Cell culture; Drug development; Neuroscience; Tissue engineering; 3D bioprinting; High-throughput screening; Biomedical engineering; Cell biology; Computer science; Stem cell; Embryonic stem cell; Drug; Chemistry; Biology; Medicine; Bioinformatics; Pathology; Disease; Pharmacology; Immunology","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":[0.0003329485,0.0004349492,0.000351732,0.0004565441,0.0002368687,0.0006053186,0.0006570619,0.0006583547,0.001601349],"category_scores_gemma":[0.0001484824,0.000297282,0.000521591,0.0002715978,0.0003073449,0.0004888349,0.0003001304,0.0004753771,0.0006715697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004849219,"about_ca_system_score_gemma":0.0004677249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001632296,"about_ca_topic_score_gemma":0.0021982,"domain_scores_codex":[0.9998201,0.00002548039,0.0000156449,0.00004054342,0.00007855823,0.00001982648],"domain_scores_gemma":[0.9998373,0.0000475244,0.00003220434,0.00004159079,0.00002339631,0.00001806903],"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":[0.00005448613,0.00008448914,0.0001372438,0.00008166445,0.00001240452,0.00009165159,0.00002374403,0.009506588,0.9848849,0.0009662936,0.0001755288,0.003981106],"study_design_scores_gemma":[0.00002678187,0.0004048694,0.0007316711,0.00001773127,0.00002761226,0.000151934,0.00001712236,0.07727924,0.9151251,0.0005422456,0.005653641,0.00002201358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5648583,0.00241805,0.418606,0.0004176548,0.0001902775,0.0003969,0.001962676,0.002429976,0.008720112],"genre_scores_gemma":[0.7642569,0.001890819,0.2246596,0.00009536815,0.00002154368,0.0004249899,0.001131983,0.00009651405,0.007422366],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001632296,"threshold_uncertainty_score":0.005357027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06376482462186935,"score_gpt":0.2883801264285875,"score_spread":0.2246153018067181,"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."}}