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Record W6938873869 · doi:10.60692/95jhd-b1175

Biochar-fertilizer mixture: does plant life history trait determine fertilizer application rate?

2023· article· en· W6938873869 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Science and Fertilization
Canadian institutionsMcGill University
Fundersnot available
KeywordsFertilizerYield (engineering)BiocharBiomass (ecology)ManureCrop yield

Abstract

fetched live from OpenAlex

The annual cumin and perennial fennel are economically important medicinal crops of cold dry regions of Pakistan. We hypothesized that the cumin, which produces 2–3 times less biomass, will respond to lower rates of mixture of biochar with synthetic NPK fertilizer or manure, compared to fennel. The NPK, poultry manure and their mixture with wood-derived or cow manure-derived biochars were applied for three consecutive years. No positive relation between application rate of biochar-mixed fertilizers and yield of both crops was observed over three years of study, except that manure-derived biochar-NPK mixture had a positive relation (R2 = 0.99, P = 0.01) with the yield of fennel only during the third year. Significant positive influences of biochar-based fertilizers compared to control were observed for cumin and fennel of third year cropping. The co-amendment of NPK (0.14 kg ha−1) with manure-derived biochar (6.6 t ha−1) consistently increased the yield of cumin during the first two years of cropping, as opposed to NPK fertilizer. Cumin had a greater seed:stover biomass ratio when it received the co-amendment of wood-derived biochar with NPK or poultry manure. Our findings indicate that there is some potential for biochar-fertilizer amendments to improve the growth of these high-value medicinal crops.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.185
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it