{"id":"W4405673947","doi":"10.1101/2024.12.16.628673","title":"PinkyCaMP a mScarlet-based calcium sensor with exceptional brightness, photostability, and multiplexing capabilities","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Japan Society for the Promotion of Science; Einstein Stiftung Berlin; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Universität Zürich; University of Tokyo; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Brightness; Multiplexing; Computer science; Calcium; Optoelectronics; Materials science; Optics; Telecommunications; 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":[0.0002014783,0.0003400908,0.0002924613,0.0002147085,0.0001380148,0.0004933672,0.0004645331,0.0005054479,0.0009674476],"category_scores_gemma":[0.0002701421,0.0001867192,0.0001713925,0.0002105957,0.0003585472,0.0004546109,0.000453893,0.0006292438,0.0008286088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005025987,"about_ca_system_score_gemma":0.0002908644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000501553,"about_ca_topic_score_gemma":0.0004258789,"domain_scores_codex":[0.9998264,0.00001373527,0.0000136385,0.00005099974,0.00007338676,0.00002191151],"domain_scores_gemma":[0.9997689,0.00003013107,0.0000603717,0.00002714471,0.00004364202,0.00006978113],"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":[0.00002188895,0.000003787369,0.00005039905,0.00002412994,0.000002388038,0.00003058604,0.000009052949,0.00006995,0.9983441,0.0001654593,0.00007666908,0.00120164],"study_design_scores_gemma":[0.000002022094,0.00001775279,0.0001828387,0.000001692753,0.000002625052,0.00009162311,0.000002645245,0.0006050927,0.9975681,0.00002233766,0.001500208,0.000003060433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352599,0.002458102,0.05232302,0.0008052569,0.0001150823,0.00009653623,0.001542451,0.0009827228,0.00641701],"genre_scores_gemma":[0.9384758,0.001419001,0.0486373,0.0002035814,0.00003178159,0.00007084425,0.001191048,0.0001601254,0.009810573],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009674476,"threshold_uncertainty_score":0.003646672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01426468349986297,"score_gpt":0.216229677370597,"score_spread":0.2019649938707341,"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."}}