{"id":"W3118694895","doi":"","title":"Development and Characterization of Calcium Sensors for In vivo Neuronal Activity Imaging","year":2018,"lang":"en","type":"article","venue":"URSCA Proceedings","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fluorescence; Fluorescent protein; Calcium; Brightness; Biophysics; Calcium imaging; In vivo; Construct (python library); Computational biology; Biology; Live cell imaging; Yellow fluorescent protein; Cell biology; Chemistry; Green fluorescent protein; Biochemistry; Cell; Computer science; Genetics; Optics; Gene; Physics","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":[0.0003966595,0.0004859829,0.0004880504,0.0002155041,0.0001634907,0.0003774819,0.0005869587,0.0005314788,0.0005778491],"category_scores_gemma":[0.0004395206,0.0002041737,0.0002474845,0.0003437946,0.0002011988,0.0003575372,0.0002236301,0.0006606165,0.0004912796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003439329,"about_ca_system_score_gemma":0.0003420393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029431,"about_ca_topic_score_gemma":0.001420556,"domain_scores_codex":[0.999792,0.00002548733,0.00001800131,0.00004259376,0.00009265629,0.00002929252],"domain_scores_gemma":[0.9997632,0.00004240876,0.00004978412,0.0000271224,0.00006953839,0.00004799249],"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":[0.00001319158,0.000007876461,0.00005758556,0.00001483795,0.00000188235,0.00001495733,0.00000591875,0.00008125451,0.9992248,0.00003664055,0.00001204571,0.0005289695],"study_design_scores_gemma":[0.000004393309,0.00008575698,0.0007416147,0.000003133684,0.000005562346,0.0000656829,0.00000785546,0.0009913963,0.9967738,0.00001700032,0.001299201,0.000004648201],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.906334,0.001113315,0.08826259,0.0001739649,0.00004802947,0.0005335967,0.001352004,0.0002942013,0.001888323],"genre_scores_gemma":[0.8028705,0.002259584,0.1838207,0.0001188678,0.00001362783,0.0007134648,0.003560311,0.0002735342,0.006369343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001029431,"threshold_uncertainty_score":0.002495408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01038738667494404,"score_gpt":0.2603262578890324,"score_spread":0.2499388712140884,"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."}}