{"id":"W6968940719","doi":"10.5281/zenodo.7227472","title":"SPI-ASAP: single-pixel imaging accelerated via swept aggregate patterns","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Aggregate (composite); Software; Feature (linguistics); Image processing","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":[0.00100214,0.003006545,0.001893699,0.002161255,0.001033567,0.001894347,0.003310178,0.001533763,0.140868],"category_scores_gemma":[0.001833891,0.001291171,0.001613922,0.00258628,0.0004087665,0.001786814,0.001855829,0.002263749,0.1391444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008310169,"about_ca_system_score_gemma":0.001515165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009246597,"about_ca_topic_score_gemma":0.01756944,"domain_scores_codex":[0.9992291,0.00006303404,0.00005835592,0.0002063171,0.0003067963,0.0001363062],"domain_scores_gemma":[0.9991078,0.0002363887,0.00007494711,0.0002405736,0.0002333717,0.0001069728],"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":[0.000157065,0.00004184151,0.0005535915,0.0007243795,0.00005655004,0.00006828892,0.00003547468,0.0009742077,0.004015077,0.0007929427,0.9848434,0.007737192],"study_design_scores_gemma":[0.0004315821,0.00007253123,0.006188803,0.0001882343,0.00007643369,0.0003588959,0.00007443772,0.007869599,0.02117715,0.006078621,0.9573065,0.0001772036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.001189125,0.0001092406,0.00661361,0.0001044203,0.00007641615,0.00006078702,0.9502739,0.03773985,0.003832709],"genre_scores_gemma":[0.002468447,0.0001066242,0.01039346,0.00009945933,0.00001457359,0.0002994648,0.9719735,0.01231214,0.002332239],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.140868,"threshold_uncertainty_score":0.4712505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691325681159536,"score_gpt":0.2459094902936113,"score_spread":0.2189962334820159,"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."}}