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Record W2137048374

Fiber Crops Program Area Research Planning and Prioritization

2000· preprint· en· W2137048374 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconstor (Econstor) · 2000
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSilkworms and Sericulture Research
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBusinessProductivityProduction (economics)SustainabilityOrder (exchange)Quality (philosophy)Industrial organizationMarketingAgricultural economicsEconomicsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

The fiber crops industry is one of the country's major pillars in employment generation and foreign exchange earnings. However, recent trade developments and local production problems in the fiber crops industry might affect its long-term sustainability and viability. The reduction of trade barriers under the GATT-WTO implies that in order for the Philippines to be globally competitive, the country must exert all efforts to increase the productivity of Philippine fiber crops, lower the cost of production, and improve the quality of fiber and fiber products through technological developments. In recent years, the increasing share of Ecuador in the world market is threatening the Philippines’ position as the top producer of abaca. Abaca farmers in Ecuador are mechanizing and producing consistent quality fibers. Unless the weaknesses and threats in the abaca industry are faced, the country's market share in the world market for abaca fiber will continue to diminish. This paper, therefore, aims to present an industry profile with focus on domestic production, consumption, external trade, problems/constraints, and market potentials; review past researches on fiber crops, technologies generated, and the extent of participation of the private and public sectors; identify research and technology gaps for the fiber crops industry; identify strengths and weaknesses in the institutional structure of research and extension interface, as well as research complementation efforts; and suggest recommendations and R & D agenda for the fiber crops industry.

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)0.001
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 score0.224
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.066
GPT teacher head0.326
Teacher spread0.260 · 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