{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001822378,0.0001760293,0.0001620754,0.0001669108,0.00009835634,0.0001270567,0.0003571762,0.0002217967,0.000005474336],"category_scores_gemma":[0.00002122292,0.0001279505,0.00003339105,0.001191393,0.00007187197,0.0001312002,0.0005030344,0.0004091395,0.00003975296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004617065,"about_ca_system_score_gemma":0.00000885118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001930267,"about_ca_topic_score_gemma":0.00003312772,"domain_scores_codex":[0.9986791,0.0000241723,0.0001720936,0.0005372473,0.0001621571,0.0004252386],"domain_scores_gemma":[0.9996712,0.00004586911,0.00002254061,0.0002114474,0.00000609352,0.00004280747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001066901,0.001075425,0.02509078,0.0002845461,0.0001703771,0.0002116538,0.005093756,0.09785824,0.2224266,0.02064578,0.06766569,0.5593705],"study_design_scores_gemma":[0.00290187,0.002099148,0.1201498,0.003544496,0.0001347689,0.001312986,0.00247553,0.5001838,0.03429404,0.1471482,0.1809503,0.004804974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9308784,0.00248777,0.06399474,0.001146738,0.0002492396,0.0003642631,0.000003034828,0.0006371549,0.0002386563],"genre_scores_gemma":[0.9190311,0.0001143636,0.08064174,0.0000647347,0.00003152927,0.00003427273,0.000004127595,0.00001080867,0.00006725186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5545655,"threshold_uncertainty_score":0.5217671,"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."}}