{"id":"W2502189175","doi":"10.3390/mi7070123","title":"Microfluidic Approaches for Manipulating, Imaging, and Screening C. elegans","year":2016,"lang":"en","type":"review","venue":"Micromachines","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; California HIV/AIDS Research Program","keywords":"Microfluidics; Caenorhabditis elegans; Phenotypic screening; Drug discovery; Nanotechnology; Biology; Computer science; Computational biology; Bioinformatics; Phenotype; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006786262,0.001027971,0.001066413,0.003327502,0.000319367,0.000915472,0.00106712,0.001003268,0.002818675],"category_scores_gemma":[0.0006751058,0.0005362038,0.0007271792,0.001959433,0.0004952373,0.00127926,0.0009366111,0.001711937,0.002628222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005533189,"about_ca_system_score_gemma":0.0009021049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009464546,"about_ca_topic_score_gemma":0.001620377,"domain_scores_codex":[0.9996589,0.00003521939,0.0000383868,0.00007005202,0.0001661456,0.00003127278],"domain_scores_gemma":[0.9997351,0.0001132455,0.00004095679,0.00001494582,0.00007174197,0.00002400006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004072336,0.00007248911,0.0002119502,0.01419125,0.00008492044,0.0001890399,0.00005974523,0.0004873995,0.0143302,0.00670889,0.0213904,0.942233],"study_design_scores_gemma":[0.00001272095,0.00009090379,0.0007079254,0.001729586,0.0001091568,0.0009685268,0.00003293407,0.0002646527,0.008739316,0.001612784,0.985684,0.00004744537],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002835501,0.9945774,0.001885875,0.0002012175,0.0002424368,0.00002132196,0.00005917233,0.0000510313,0.002677963],"genre_scores_gemma":[0.001466107,0.9950764,0.001554369,0.0001708095,0.0001091827,0.00002985305,0.00007920179,0.00000533386,0.001508809],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003327502,"threshold_uncertainty_score":0.009429395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04707029906348514,"score_gpt":0.2943736188798598,"score_spread":0.2473033198163747,"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."}}