{"id":"W6977698016","doi":"10.7298/361v-c453","title":"MOLECULAR AND DATA ANALYSIS METHODS TO EXPAND THE SCOPE OF SINGLE-CELL TRANSCRIPTOMICS","year":2022,"lang":"en","type":"article","venue":"eCommons (Cornell University)","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Scope (computer science); Transcriptome; The Internet; Key (lock); Big data","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021009,0.0007986504,0.0006121218,0.001745353,0.0004298261,0.002836448,0.0006940577,0.0006503599,0.01269101],"category_scores_gemma":[0.002535648,0.0005953177,0.0007039775,0.001042429,0.0009814258,0.001405748,0.001072697,0.002347447,0.005139233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005445479,"about_ca_system_score_gemma":0.0008360939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005633716,"about_ca_topic_score_gemma":0.001377861,"domain_scores_codex":[0.9991103,0.0001366793,0.00009019134,0.0001901287,0.0004377564,0.00003501732],"domain_scores_gemma":[0.9979959,0.0009992643,0.00009537792,0.0004510547,0.0003520098,0.0001064558],"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":[0.000123479,0.000163826,0.001316998,0.0005275129,0.00007934858,0.0001920744,0.0001318744,0.001365084,0.5687372,0.02602228,0.02626962,0.3750707],"study_design_scores_gemma":[0.00004696186,0.0001347804,0.004732177,0.00025822,0.0001336168,0.0005968362,0.00009687676,0.05892763,0.5696966,0.04678932,0.3184458,0.0001412353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009201104,0.005182217,0.9534667,0.002977826,0.002418105,0.0002557875,0.003798115,0.0106106,0.01208942],"genre_scores_gemma":[0.0759832,0.009135577,0.8562261,0.002150636,0.001465495,0.0008189941,0.008891797,0.003297556,0.04203055],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01269101,"threshold_uncertainty_score":0.04245567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0480887129656812,"score_gpt":0.2240036416942957,"score_spread":0.1759149287286144,"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."}}