{"id":"W4402827759","doi":"10.1016/j.compag.2024.109451","title":"A multi-faceted decision-making approach to feasible hydroponic technology acquisition","year":2024,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Engineering; Industrial engineering; Systems engineering; Agricultural engineering; Manufacturing engineering","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":[0.01101318,0.001774261,0.002733031,0.003030656,0.002476372,0.008875008,0.003939101,0.003282989,0.01119494],"category_scores_gemma":[0.01675054,0.001579318,0.002546453,0.002635522,0.002482237,0.004567373,0.005579489,0.002619031,0.000719486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003853584,"about_ca_system_score_gemma":0.007578414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007683909,"about_ca_topic_score_gemma":0.01002347,"domain_scores_codex":[0.9897132,0.005781364,0.0005837328,0.001150576,0.001811709,0.0009593172],"domain_scores_gemma":[0.9889117,0.007904422,0.0007303256,0.0004536886,0.001312913,0.0006868981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004138113,0.0006080769,0.002835707,0.0005542387,0.0004988266,0.0006758571,0.001257931,0.8274718,0.003906458,0.05474881,0.002025715,0.1050027],"study_design_scores_gemma":[0.00005867936,0.0002989018,0.0006996156,0.000103614,0.0000980042,0.00007096425,0.0007408713,0.9116251,0.001182776,0.0830709,0.001975602,0.00007482628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0311277,0.0002195243,0.9510277,0.00137395,0.00005044476,0.0009121287,0.0003081694,0.0002240073,0.01475644],"genre_scores_gemma":[0.4788265,0.0002097909,0.5176398,0.0002023167,0.00005970419,0.0009497169,0.0002770571,0.00005444637,0.001780629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01119494,"threshold_uncertainty_score":0.05824393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097942571226231,"score_gpt":0.2557263952280409,"score_spread":0.2447469695157786,"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."}}