{"id":"W4394346602","doi":"10.6084/m9.figshare.20341392","title":"Antibiotics Experiment - Cell sorting","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Sorting; Antibiotics; Computer science; Computational biology; Biology; Microbiology; Programming language","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":[0.002884836,0.003638544,0.002957347,0.003240182,0.001631369,0.003706149,0.004167689,0.003732735,0.1053794],"category_scores_gemma":[0.01178183,0.0008287071,0.0023555,0.004630384,0.0005963075,0.001674045,0.002132439,0.002868791,0.1137636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001566913,"about_ca_system_score_gemma":0.003788199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007315132,"about_ca_topic_score_gemma":0.01610393,"domain_scores_codex":[0.9971752,0.0004622373,0.0003403179,0.001118473,0.0005526203,0.0003510367],"domain_scores_gemma":[0.9962565,0.001395459,0.0002811527,0.0009018215,0.0008728584,0.0002922798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004520919,0.0001139929,0.003507749,0.004137315,0.0002160554,0.00006389568,0.00005668202,0.0009587823,0.001538214,0.001344358,0.9794057,0.008205253],"study_design_scores_gemma":[0.0007257108,0.00007822241,0.003927278,0.0005850094,0.0001679378,0.00007826069,0.00007118558,0.0007971346,0.002323943,0.002347923,0.9888421,0.00005523795],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003584512,0.0002019459,0.0002676978,0.00007604948,0.00005810544,0.00005346577,0.9968928,0.001036612,0.001054814],"genre_scores_gemma":[0.000750704,0.0001393294,0.001401638,0.0001400442,0.00001364046,0.0003667269,0.9958572,0.0002594299,0.001071227],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1053794,"threshold_uncertainty_score":0.352529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02423881168809735,"score_gpt":0.2554277078226656,"score_spread":0.2311888961345683,"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."}}