{"id":"W2610682758","doi":"10.1145/3027063.3053192","title":"Save the Kiwi","year":2017,"lang":"en","type":"article","venue":"","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Food waste; Kiwi; Sustainability; Work (physics); Exploratory research; Computer science; Food packaging; Business; Environmental economics; Engineering; Waste management; Food 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":[0.0004772716,0.0007975677,0.0003018191,0.0008647969,0.001691192,0.002521434,0.001051769,0.0015001,0.04678206],"category_scores_gemma":[0.002617582,0.0002688889,0.0004802933,0.0005433213,0.0006793021,0.004560837,0.002794875,0.001135721,0.02126669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003924984,"about_ca_system_score_gemma":0.0006469499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001095433,"about_ca_topic_score_gemma":0.002301199,"domain_scores_codex":[0.9996932,0.00006735275,0.00001639853,0.00004851643,0.0001111672,0.00006332777],"domain_scores_gemma":[0.99937,0.0001412817,0.00005042785,0.0001117565,0.000169455,0.000157136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006530217,0.0004095766,0.00574397,0.001400877,0.00005630849,0.0009908489,0.00952648,0.000533598,0.01668694,0.05550448,0.2300682,0.6784256],"study_design_scores_gemma":[0.00002017932,0.0001474812,0.002218742,0.0001962383,0.00004152121,0.0007220178,0.001836469,0.001025268,0.003878841,0.006445304,0.9834133,0.00005474046],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1271726,0.003924976,0.112925,0.01153479,0.002845555,0.0009803294,0.002659107,0.02064245,0.7173153],"genre_scores_gemma":[0.3784854,0.003952035,0.09675135,0.003511873,0.0004949733,0.0008476659,0.003383251,0.001980203,0.5105932],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04678206,"threshold_uncertainty_score":0.1565015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287953899660039,"score_gpt":0.3123116717600614,"score_spread":0.279432132763461,"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."}}