{"id":"W6968956608","doi":"10.5281/zenodo.5156215","title":"Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data - Basel processed data","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute","funders":"","keywords":"Identity (music); Multiplexing; Expression (computer science); Pattern recognition (psychology); Cell","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":[0.002238176,0.001003127,0.0008233822,0.00291651,0.0008072732,0.002197458,0.0005594296,0.0006245241,0.01032837],"category_scores_gemma":[0.002790714,0.0005042612,0.000720726,0.002369385,0.0005104002,0.0006959212,0.001141027,0.0007677528,0.006723986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006584831,"about_ca_system_score_gemma":0.001309826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002484293,"about_ca_topic_score_gemma":0.005436854,"domain_scores_codex":[0.9988484,0.00007596141,0.0001036493,0.0004718878,0.0003335278,0.0001665437],"domain_scores_gemma":[0.9988494,0.000280387,0.0001346685,0.0003178341,0.0003609358,0.00005674622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002272339,0.0001649165,0.05925575,0.001027102,0.0003346054,0.0005382357,0.0008814921,0.002486841,0.7323843,0.002289061,0.04165167,0.1567136],"study_design_scores_gemma":[0.0001117667,0.0002785298,0.2560889,0.0002281769,0.0003150833,0.002076608,0.0008782716,0.04057519,0.5890607,0.004793529,0.1053325,0.0002607884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.3840725,0.002284299,0.291325,0.0009256685,0.000687266,0.0006143519,0.268073,0.03872315,0.01329478],"genre_scores_gemma":[0.3958234,0.001266503,0.3825095,0.0003839148,0.0001691246,0.002485101,0.1994644,0.006579538,0.0113186],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01032837,"threshold_uncertainty_score":0.03455186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0525153999698243,"score_gpt":0.256697807919481,"score_spread":0.2041824079496568,"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."}}