{"id":"W7086917671","doi":"10.5281/zenodo.15678602","title":"MERFISH 4T1 Tissue Raw Unaligned Images","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Vancouver Coastal Health; University of British Columbia; BC Cancer Agency","funders":"","keywords":"Field (mathematics); Medical imaging; Image resolution; Resolution (logic); Preclinical imaging; High resolution","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":[0.0008166646,0.003659723,0.001826324,0.002648062,0.0008133662,0.001798915,0.003019908,0.002631217,0.02184768],"category_scores_gemma":[0.002106024,0.0007231654,0.001959363,0.002684186,0.0006235797,0.0009298797,0.001812403,0.001525729,0.04231369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216642,"about_ca_system_score_gemma":0.00149281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01453688,"about_ca_topic_score_gemma":0.03485756,"domain_scores_codex":[0.9990063,0.00008933256,0.00007356844,0.0003890941,0.0002933578,0.0001483821],"domain_scores_gemma":[0.9993165,0.0001206246,0.00006659611,0.0002329279,0.0001967878,0.00006657395],"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":[0.0007106305,0.0001834546,0.003357479,0.002828331,0.0003552761,0.0004748501,0.00005938183,0.003942142,0.009081812,0.0006766046,0.9461864,0.03214362],"study_design_scores_gemma":[0.0005135119,0.0002280348,0.02153476,0.0008007316,0.0003024905,0.002232027,0.000183535,0.008305489,0.01471557,0.002723226,0.9482871,0.000173532],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003520244,0.001023316,0.001113876,0.0001250708,0.00009445142,0.00007905142,0.9892254,0.003007201,0.001811241],"genre_scores_gemma":[0.002021319,0.0001633266,0.001181555,0.00003974708,0.000008510433,0.00007260214,0.9955311,0.0001392499,0.0008426],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02184768,"threshold_uncertainty_score":0.07308769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03554226789850085,"score_gpt":0.2759483198012135,"score_spread":0.2404060519027127,"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."}}