{"id":"W2953970248","doi":"10.1007/s13762-019-02442-z","title":"Seaweed extract: biostimulator of plant defense and plant productivity","year":2019,"lang":"en","type":"article","venue":"International Journal of Environmental Science and Technology","topic":"Plant Growth Enhancement Techniques","field":"Agricultural and Biological Sciences","cited_by":196,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Agriculture; Fertilizer; Muck; Productivity; Crop productivity; Environmental science; Algae; Nutrient; Agronomy; Seedling; Environmentally friendly; Biology; Crop; Agroforestry; Botany; Ecology","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":[0.0003425795,0.0000666024,0.0001182676,0.00009105064,0.00003601022,0.00001496529,0.0003159568,0.00005081651,0.00005444989],"category_scores_gemma":[0.00004856267,0.00002954116,0.00001609685,0.0001286622,0.0004404614,0.0002582259,0.0001632629,0.00009611612,0.000002222193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003821466,"about_ca_system_score_gemma":0.0000099682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009592905,"about_ca_topic_score_gemma":0.000006300592,"domain_scores_codex":[0.9991526,0.000007974979,0.0001856921,0.0001547425,0.0003863267,0.0001126643],"domain_scores_gemma":[0.999639,0.000046505,0.0002045487,0.00003076902,0.00003738813,0.00004178229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003087694,0.00006115188,0.06721181,0.000001072903,0.000008137396,0.000009528673,0.00001279416,2.031538e-7,0.8868979,0.0002854739,0.0000179004,0.04546319],"study_design_scores_gemma":[0.0002675148,0.0007673604,0.2606384,0.00005436403,0.00000888148,0.0008678108,0.0002116474,0.000078474,0.7297769,0.001171404,0.006028277,0.0001289928],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998217,0.0001675915,0.000001998333,0.001202785,0.0001078843,0.00008773144,0.0001064384,0.000009835806,0.00009869137],"genre_scores_gemma":[0.999465,0.0002553778,0.0001967576,0.00002895241,0.00002815934,8.849462e-7,0.000003924914,4.120348e-7,0.00002052563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1934266,"threshold_uncertainty_score":0.1622898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006909132987449473,"score_gpt":0.2009501591702479,"score_spread":0.1940410261827984,"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."}}