{"id":"W4211105715","doi":"10.21203/rs.3.rs-1287670/v1","title":"Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Graph; Artificial intelligence; Autoencoder; Machine learning; Benchmark (surveying); Deep learning; Theoretical computer science; Cartography","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":[0.000971883,0.0008805811,0.0007763614,0.001354459,0.0002713325,0.0007986408,0.00111552,0.0009701534,0.001085594],"category_scores_gemma":[0.002004314,0.0004307289,0.001278539,0.0009665668,0.000571414,0.0009031055,0.001203155,0.001074133,0.0004058756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006213316,"about_ca_system_score_gemma":0.0006670408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007064535,"about_ca_topic_score_gemma":0.01080293,"domain_scores_codex":[0.9995841,0.00007385175,0.00001407091,0.0001891386,0.00008766633,0.0000510934],"domain_scores_gemma":[0.9992287,0.0003288499,0.0001025034,0.0001307212,0.0001367233,0.00007236486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002800726,0.0001395994,0.007319552,0.0002081741,0.0002731732,0.0003135541,0.0001904088,0.700717,0.07852454,0.005362621,0.005296385,0.2013749],"study_design_scores_gemma":[0.000005274006,0.00001719318,0.0006658357,0.0000047027,0.00001770851,0.0000297572,0.00001356546,0.9915863,0.004272779,0.002924171,0.0004542036,0.000008535652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04995543,0.0004129267,0.9465036,0.0001877499,0.00003434428,0.00003527847,0.0003965737,0.001815591,0.000658526],"genre_scores_gemma":[0.7478144,0.0004246765,0.2467054,0.0002237801,0.00006850912,0.000101923,0.002140584,0.0003512362,0.002169482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007064535,"threshold_uncertainty_score":0.01404679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09434789386799103,"score_gpt":0.3777486904788206,"score_spread":0.2834007966108296,"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."}}