{"id":"W2588815320","doi":"10.1038/nmicrobiol.2017.18","title":"CRISPR–Cas in the laboratory classroom","year":2017,"lang":"en","type":"article","venue":"Nature Microbiology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"CRISPR; Archaea; Nucleic acid; Biology; Computational biology; Bacteria; Trans-activating crRNA; Genetics; Gene; Microbiology; Genome editing","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":[0.00363693,0.0006383787,0.0007344557,0.0006642881,0.001664801,0.003752756,0.002083837,0.002561528,0.03642062],"category_scores_gemma":[0.003197774,0.0004086718,0.0004626526,0.0003578919,0.002726268,0.003969756,0.004950306,0.006456503,0.01291668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709218,"about_ca_system_score_gemma":0.003242221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004016596,"about_ca_topic_score_gemma":0.001016178,"domain_scores_codex":[0.9977704,0.0005890458,0.00007145242,0.0005967827,0.0007044122,0.0002679056],"domain_scores_gemma":[0.994866,0.0009776347,0.0002660848,0.0008880501,0.0004769005,0.002525265],"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":[0.0007712842,0.00202084,0.002633019,0.0004776396,0.00005989018,0.0007208331,0.001943433,0.001422894,0.1748857,0.1663496,0.2035001,0.4452147],"study_design_scores_gemma":[0.0001905877,0.0006485058,0.002351982,0.0002410945,0.00003441038,0.0008778252,0.001698035,0.002220367,0.05098529,0.1852474,0.7554135,0.00009098826],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.08372691,0.01770803,0.3380023,0.1332266,0.01147236,0.000324326,0.000996899,0.01311743,0.4014252],"genre_scores_gemma":[0.501812,0.01190502,0.1969367,0.02521846,0.005652759,0.0004889877,0.0008185615,0.001762252,0.2554052],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03642062,"threshold_uncertainty_score":0.1218391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004010651564084817,"score_gpt":0.3057412596207237,"score_spread":0.3017306080566389,"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."}}