{"id":"W4396945066","doi":"10.48550/arxiv.2405.08717","title":"How Much You Ate? Food Portion Estimation on Spoons","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Estimation; Statistics; Economics; Mathematics; Management","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001252636,0.0004921779,0.0002805815,0.0006957882,0.0001646547,0.0003896579,0.000230018,0.0003790122,0.004244188],"category_scores_gemma":[0.0006709974,0.0001289308,0.0001806744,0.0006119381,0.0000860795,0.0004005336,0.0002605645,0.0001862057,0.002026658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001421475,"about_ca_system_score_gemma":0.0001197323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002692747,"about_ca_topic_score_gemma":0.00558473,"domain_scores_codex":[0.9998339,0.00001813277,0.000006213235,0.00006595609,0.00005356774,0.00002220047],"domain_scores_gemma":[0.9998251,0.00004447515,0.00002885609,0.00001126009,0.00007478957,0.00001563084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002455784,0.0002263967,0.08399468,0.0007363511,0.0001140042,0.0007374545,0.0006256928,0.003601268,0.2526983,0.0009445441,0.01267929,0.6411863],"study_design_scores_gemma":[0.00005167202,0.0006427434,0.4871784,0.0002181211,0.0001652923,0.001979023,0.001545742,0.2701027,0.2058556,0.002012135,0.03008437,0.0001641125],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7706203,0.001383589,0.1932034,0.0002495415,0.0002208901,0.0002289314,0.006326039,0.002909746,0.02485746],"genre_scores_gemma":[0.8804592,0.001009361,0.1000049,0.0002579615,0.00005498108,0.0001560315,0.003734506,0.0001757954,0.01414717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004244188,"threshold_uncertainty_score":0.01419818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845186708966252,"score_gpt":0.1667897329144646,"score_spread":0.1183378658248021,"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."}}