{"id":"W2945908058","doi":"10.1101/637652","title":"A zero-inflated gamma model for post-deconvolved calcium imaging traces","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; Canada Research Chairs; Gatsby Charitable Foundation; Charles H. Revson Foundation; National Institutes of Health; National Science Foundation","keywords":"Calcium imaging; Context (archaeology); Calcium; Statistical model; Poisson distribution; Neural activity; Artificial neural network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004949057,0.0007686927,0.0007044032,0.0003753122,0.0002959219,0.0005264338,0.0008599095,0.0004778284,0.00002070923],"category_scores_gemma":[0.0007049608,0.0007933518,0.0003743371,0.000377411,0.0001343158,0.0004146487,0.0004809673,0.0008634989,0.00009232101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002729809,"about_ca_system_score_gemma":0.0006109661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003178287,"about_ca_topic_score_gemma":0.000001958025,"domain_scores_codex":[0.995889,0.0001241127,0.0007215278,0.00188103,0.0004618547,0.0009224457],"domain_scores_gemma":[0.9969044,0.0002662177,0.0006294956,0.001348538,0.0005631105,0.0002881981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001186199,0.00009494314,0.000541513,0.0003573927,0.00002791483,0.00002366058,0.000011039,0.005572004,0.9919065,0.0009916199,0.0003492821,0.000005474113],"study_design_scores_gemma":[0.0006889792,0.00005214884,0.00226353,0.0001594886,0.00007752544,3.936067e-8,0.000001065591,0.6229882,0.3722513,0.00002712749,0.0006907508,0.0007999013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9459379,0.0001797856,0.0456592,0.0008030007,0.003272749,0.002276133,0.001085825,0.0007691242,0.00001623082],"genre_scores_gemma":[0.9958212,0.00006689963,0.00160818,0.001554564,0.0002790775,0.0003396065,0.000001325163,0.0002391716,0.00008991751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6196553,"threshold_uncertainty_score":0.9994518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034584487823925,"score_gpt":0.2444357808797559,"score_spread":0.2140899360015167,"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."}}