{"id":"W4387346784","doi":"10.1088/1757-899x/1291/1/012030","title":"PLC-based Automated Aqua-Hydroponics System","year":2023,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Aquaponics; Environmental science; Nutrient; Hydroponics; Plant growth; Ipomoea aquatica; Humidity; Spinach; Fish <Actinopterygii>; Agricultural engineering; Environmental engineering; Agronomy; Biology; Ecology; Engineering; Aquaculture","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":[0.0003308614,0.0006454496,0.0004685346,0.0007511918,0.0002921425,0.0006049999,0.001317431,0.0004236282,0.01883908],"category_scores_gemma":[0.0004740506,0.0002573458,0.0002031659,0.0003554213,0.0002241025,0.000572846,0.0005329707,0.0003032008,0.004335792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004360065,"about_ca_system_score_gemma":0.0005591244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002386804,"about_ca_topic_score_gemma":0.001420463,"domain_scores_codex":[0.9993713,0.00007248847,0.00004975113,0.0002173633,0.0002364561,0.00005255238],"domain_scores_gemma":[0.9994992,0.00008896123,0.00007371094,0.00008150285,0.0002086475,0.00004795118],"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":[0.002681398,0.001146653,0.02348877,0.001518559,0.0001647055,0.001424464,0.0005411246,0.02921319,0.2556784,0.002889971,0.0662244,0.6150284],"study_design_scores_gemma":[0.001281665,0.003096269,0.02666336,0.0002352324,0.0003525657,0.002533851,0.0002698826,0.5699741,0.244835,0.002626811,0.1478119,0.000319304],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.242255,0.0008280192,0.5218024,0.0008225869,0.0005316366,0.001756681,0.004897743,0.178635,0.04847097],"genre_scores_gemma":[0.9262087,0.0001970949,0.04507263,0.0003648693,0.0001136739,0.0005614827,0.001596028,0.0003741951,0.02551124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01883908,"threshold_uncertainty_score":0.06302303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216416425678102,"score_gpt":0.2319420306059602,"score_spread":0.2097778663491792,"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."}}