{"id":"W4413318797","doi":"10.1109/tmc.2025.3599917","title":"RipeTrack: Assessing Fruit Ripeness and Remaining Lifetime Using Smartphones","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ripeness; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002314003,0.000917479,0.0006418683,0.001278015,0.0001443159,0.0004780712,0.0005362631,0.0007443879,0.00189932],"category_scores_gemma":[0.0009911758,0.000162447,0.0003576771,0.0005321334,0.00008994217,0.0006177739,0.0004947027,0.0002445924,0.001179448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002105867,"about_ca_system_score_gemma":0.0001342398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003265749,"about_ca_topic_score_gemma":0.006555465,"domain_scores_codex":[0.9997712,0.00001970706,0.00002047803,0.00008353415,0.00007926176,0.00002587382],"domain_scores_gemma":[0.9994631,0.0001453011,0.0001218375,0.00005273725,0.0001693693,0.00004746219],"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":[0.003086229,0.0006704325,0.2640847,0.002377325,0.0006109946,0.001568381,0.0004844313,0.0154163,0.1657112,0.0007794506,0.02339254,0.5218181],"study_design_scores_gemma":[0.0001376402,0.001896561,0.5040768,0.0002165403,0.0004247779,0.002635788,0.0009471398,0.3755057,0.09781342,0.001218281,0.0148482,0.000279135],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8924407,0.002676837,0.06650685,0.0003063589,0.0001862139,0.0004938419,0.01508409,0.01272266,0.00958251],"genre_scores_gemma":[0.9419808,0.0007451751,0.04699986,0.0002458523,0.00006121014,0.0002146879,0.005609353,0.0001136409,0.004029378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003265749,"threshold_uncertainty_score":0.006493449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03647660004323944,"score_gpt":0.3164903274517235,"score_spread":0.2800137274084841,"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."}}