{"id":"W4402775819","doi":"10.17504/protocols.io.14egn6opyl5d/v1","title":"Tissue preparation and tissue imaging for MERFISH v1","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Cardiovascular Disease and Adiposity","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Biomedical engineering; Medicine; Computer science","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":[0.0010954,0.0009611941,0.0005010735,0.001262459,0.0009973561,0.0008578998,0.0007982327,0.001385341,0.04781265],"category_scores_gemma":[0.001024873,0.001127998,0.0006174692,0.0005816591,0.000568276,0.0007840284,0.0008000745,0.00174848,0.01487291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005351446,"about_ca_system_score_gemma":0.001108441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002374744,"about_ca_topic_score_gemma":0.007333732,"domain_scores_codex":[0.9994631,0.00002521766,0.00004126041,0.0002332075,0.0001693955,0.00006775195],"domain_scores_gemma":[0.9993266,0.0001155428,0.00005303709,0.0002027251,0.0002109598,0.00009117019],"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":[0.0004491615,0.00005126899,0.001787602,0.0004334057,0.00003436104,0.0002796882,0.00023015,0.0005098133,0.9630023,0.001692842,0.01114973,0.02037966],"study_design_scores_gemma":[0.0001895606,0.000554465,0.03084408,0.000303119,0.0001327386,0.0027838,0.0002831928,0.005944593,0.7099405,0.002327855,0.2465678,0.0001283025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2322589,0.002555541,0.614455,0.001083963,0.001011239,0.005915883,0.06430671,0.02033085,0.05808188],"genre_scores_gemma":[0.1507539,0.001861422,0.644625,0.00136645,0.0001383128,0.007700382,0.05288799,0.01163929,0.1290272],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04781265,"threshold_uncertainty_score":0.1599492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186889221238743,"score_gpt":0.3194123667340525,"score_spread":0.3075434745216651,"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."}}